title:PovertyandSocialDevelopmentsinPeru,1994-1997WorldBankCountryStudy,0253-2123

author:publisher: WorldBank

isbn10|asin: 0821344927printisbn13: 9780821344927ebookisbn13: 9780585183268

language: English

subject Poverty--Peru,Peru--Socialconditions--1968-

publicationdate: 1999lcc: HC230.P6P681999ebddc: 362.5/0984

subject: Poverty--Peru,Peru--Socialconditions--1968-

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PovertyandSocialDevelopmentsinPeru,19941997

AWORLDBANKCOUNTRYSTUDY

TheWorldBankWashington,D.C.

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Copyright©1999TheInternationalBankforReconstructionandDevelopment/THEWORLDBANK1818HStreet,N.W.Washington,D.C.20433,U.S.A.

AllrightsreservedManufacturedintheUnitedStatesofAmericaFirstprintingMay1999

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ISSN:0253-2123

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ContentsBasicIndicators iv

CurrencyEquivalents,GovernmentFiscalYear,andAcronymsandAbbreviations

v

Abstract vi

Acknowledgments viii

PobrezayDesarrolloSocial,19941997:ResumendelInforme

ix

1.Overview 1

PovertyandSocialDevelopments,19941997 1

WhatHelpsHouseholdsAdvance? 2

ProspectsforPovertyReduction-GrowthandEmploymentLinks

3

SocialExpenditure 4

FromIndividualSectorStrategiestoaConsistentandBroad-basedAnti-PovertyFocus

4

Outline 5

2.PovertyRatesasPolicyGoals? 6

3.Poverty,Inequality,andSocialDevelopments,19941997

8

BasicDevelopments 8

RegionalDevelopments 12

InequalityandItsComponents 15

4.Poverty-ChangingFaces? 18

PovertyComparisonsHowDidGroupsinSocietyFare? 19

PovertyComparisonsKeyFactorsinWelfareChanges 25

5.GrowthandEmployment 32

LaborMarketTrends 32

GrowthPattern,PovertyReduction,andSectorEmploymentGrowth

33

GrowthandPovertyReduction:Simulations 34

TheTaskAhead:RaisingProductivityandRealIncomes

36

6.SocialExpenditures-WhatandforWhom? 37

SocialExpendituresin1996 37

PovertyImpactsofDirectTransfers 42

7.Institutions-FromIndividualSectorStrategiestoaConsistentandBroad-basedAnti-povertyFocus

44

References 47

Annex1:PanelStudyofHouseholds 50

Annex2:Methodology 53

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BasicIndicatorsTableGeneral

Area,land1 sqkm,thousands 1,280Population,19961 millions 24.2

growthrate,198019961

percentperannum 2.1

density,19961 persqkm 18.7SocialIndicators

malnutrition,chronic,19972

percentofchildrenbelowfiveyears 23.8

infantmortality,19961

per1000livebirths 42.0

under-fivemortality,19961

per1000 58.0

adolescentfertilityrate,19951

birthper1,000womenage1519 52.0

totalfertilityrate,19961

birthsperwomen 3.1

lifeexpectancytbirth,19961

years 68.0

literacyrate,19972 populationage6andover 90.2netenrollmentrates3

urbanprimary2 percentofrelevantagegroup 90.0ruralprimary2 percentofrelevantagegroup 88.0urbansecondary2

percentrelevantagegroup 78.0

ruralsecondary2 percentofrelevantagegroup 49.0povertyincidence,19972

percent 49.0

povertygap,19972 percent 16.0severepoverty percent 14.8

incidence,19972incomeinequality,total,19972

Ginicoefficient .484

childlabor,19972 percentofchildren,age6to14,workingmorethan15hrsperweek

11.8

electricityconnections,19972

percentofpopulation 73.7

sanitationconnections,19972

percentofpopulation 58.6

water,publicnet,19972

percentofpopulation 72.8

EconomicIndicatorsGNPpercapita,19983

$US 2,497

GDPgrowth,19983 percent 0.70Inflation,19983 percent(endofperiod) 6.01budgetbalance,19983

consolidatedNFPSas%ofGDP -0.6

currentaccount,19983

percentofGDP -6.0

1WorldBank(1998),WorldDevelopmentIndicators,WashingtonD.C.2StaffestimatesbasedonInstitutoCuánto(1997),EncuestaNacionaldeHogaressobreMedicióndeNivelesdeVida,Lima.3WorldBankestimatesbasedondatafromCentralBankofPeru.

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CurrencyEquivalentsCurrencyUnit-NuevoSol

US$1.00=3.33soles(March31,1999)

GovernmentFISCALYEARJanuary1toDecember31

AcronymsandAbbreviations

BanMat BancodeMateriales

CIAS ConsejoInterministerialdeAsuntosSociales

COOPOP OficinadeCooperaciónPopular

ENACE EmpresaNacionaldeEdificaciones

ENAHO EncuestaNacionaldeHogares

ENHOVI EncuestadeHogaressobreViolencia

ENNIV EncuestaNacionaldeHogaressobreMedicióndeNivelesdeVida

FONAVI FondoNacionaldeVivienda

FONCODESFondoNacionaldeCompensaciónyDesarrolloSocial

GRADE GrupodeAnálisisparaelDesarrollo

IDB Inter-AmericanDevelopmentBank

INABIF InstitutoNacionaldeBienestarFamiliar

INEI InstitutoNacionaldeEstadísticaeInformática

IMF InternationalMonetaryFund

INFES InfraestructuraNacionalParaEducaciónySalud

IPSS InstitutoPeruanodeSeguridadSocial

LSMS LivingStandardMeasurementSurvey

MECOVI ProgramaparaelMejoramientodelasEncuestasylaMedicióndelasCondicionesdeVida

PACFO ProgramadeComplementaciónAlimentariaparaGruposenMayorRiesgo

PAR ProyectodeApoyoalReboplamientoyDesarrollodeZonasdeEmergencia

PRONAA ProgramaNacionaldeAsistenciaAlimentaria

USAID UnitedStatesAgencyforInternationalDevelopment

Ute-FONAVI

UnidadTécnica-FondoNacionaldeVivienda

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AbstractThisreportevaluatessocialprogressinPerufrom1994to1997.Itcarriesmainlygoodnewsbutalsoreportsseveralworrisomedevelopments.Thegoodnewsisthatsocialwelfareimprovedoverthethreeyears-andthisistruewhenlookedatfromavarietyofangles.Thepovertyratedeclinedbyseveralpercentagepointsandstoodat49percentin1997.Severepovertyalsodeclined,fromabout19to15percent.Schoolattendanceroseslightly,literacyratesincreasedfrom87to90percent,andthepopulationishealthier.Mostimportantamongthelatter,therateofmalnutritionforchildrenbelowtheageoffivefurtherdropped.Theseimprovementsarewithoutdoubtduetothefavorableoveralleconomicenvironment,withpercapitarealgrowthratesfrom1994to1997atabout3.5percent.Weestimatethatabout1.3millionadditionaljobswerecreatedintheeconomy,absorbingbothapopulationincreaseandahigherparticipationrateinthelaborforce.Manyofthesenewjobsareinformaljobs,however,soworkersarewithoutformalcontracts,pensioninsurance,orhealthinsurance.InformalityinPeruremainsataconstantrateofabout45percentofurbanemployment,evenhigherinruralareas.

Buttherearealsosomeworrisomedevelopmentstoreport-andmostofthemarecloselyknittogether.EconomicgrowthandGovernmentprogramshavenotbeenspreadequallyandhavenotbenefitedeverybody.First,regionaldisparitieshavegrown,withsomeregionsshowingenormousprogress,especiallyLima,andotherregionsfallingrelativelybehind,especiallytheruralareasinthehighlands.Thisdifferentregionaldevelopmentisalsomirroredinthedistributionofmajorpublicinvestments:Whilethegovernmenthasmadeanefforttoreachoutmoretothemarginalruralpopulation,thisefforthasonlypartiallytranslatedintomeasurablebenefits.Ofthe

largeachievementsineducation,healthandinfrastructure,about70percenthavebeenincities.IninternationalcomparisonsPeruremainsoneofthecountrieswithanextremelyhighvariationofregionalincome.

Second,withregionaldisparitiesincreasingwealsofindsomeevidencethatinequalityhasriseninthethreeyearsunderstudy-asmallincreaseininequalitycanbeobservedwhenusingseveralmeasurementmethodsandwhenlookingatthedistributionofincomeorwealthalike.

Third,Peru'sdevelopmentinthepastyearshasbeeninclusiveformanybutexclusiveforothers.Whilewefindgenderdifferencesnarrowingandvulnerablegroupssuchasmigrantsandthelandlesssharingthebenefitsofdevelopment,certaingroupsappeartohavefallenfurtherbehindorremainhighlyatriskofdeprivation.Onegroupisclearlytheindigenouspopulation.Theirsocialandpoliticalintegrationisstillfarfromachieved.Similarly,thesocialsituationofchildrenremainsbleak.

Anumberoffactorshaveinfluencedhouseholdwelfareovertime,inbothpositiveandnegativeways.First,surprisingly,householdsweremorelikelytoadvanceiftheirincomestemmedfromtheinformalsectorthanfromtheformalsector.Thisistrueinurbanareasaswellasininformaloff-farmemploymentinruralareas.Second,householdsizematters.Largerfamilieshavedoneworsethansmallerones-thisrelationshipcanworkthroughhigherdependencyratiosthatcanlimittheabilityofhouseholdstosave.Third,moreeducationmeansfasteradvancement.Finally,savingsandaccesstobasicserviceslikewater,electricityorsanitationisnotonlyofimmediatesupporttohouseholdsbuthelpsthemadvancefasterinwaysnotjustdirectlyconnectedtoservicesaccess.Wealsofindthatbundlingofsuchservices

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matters:providingtwoservicesjointlyhasamorepositiveeffectthanthesumofprovidingeachoneseparately.

Onfacevalue,Peru'sgrowthpathoverthepastyearswaspro-poorbecausethesectorswhereworkersandtheirdependentsaremostlikelytobepoor(construction,commerceandagriculture)grewfastest.Thisappearstohavehelpedthepoorinconstructionandcommerce.Inagriculture,however,povertyreductionwasslowerthancouldhavebeenhopedfor.Employmentcreationasacorollarytoagriculturalgrowthwasnotstrong.Thiscouldbeduetoaproductivitybacklogstemmingfromtherecessionatthebeginningofthe1990s,implyingthatagriculturalgrowthfirstledtomoreintensivework,i.e.longerhoursperemployedperson.

AnumberofsimulationsshowhowimportantgrowthremainsforpovertyreductioninPeru.Thesimulationsdoshow,however,thatthetypeofgrowthanditsregionaldistributionwillmatter-themoregrowthisbasedinagriculture,constructionandcommerce,andthemoreitsimpactsfilterthroughtotheruralhighlandsandlowlands,themorepovertywillbereducedintheshortrun.Whilethegrowthpatternshouldnotbeartificiallytiltedtowardssuchsectors,investmentinthesesectorswilldependonacontinuationofnondiscriminationpolicies.

Thedistributionofsocialandanti-povertyexpenditureshasbeendisappointing.Thedistributionof7.6billionsoles(about40percentofthetotalpublicbudgetin1996)ismildlytiltedtowardsthebetter-offinPeruviansociety;i.e.,thepoorestobtainlessoftheseexpendituresthantheirpopulationshare.Inlargepartthisisduetotheanti-poordistributionofhighereducationandhospitalexpenditures.SeveralspecializedGovernmentprogramsreachonlyasmallproportionofthepooranddirectpublictransfersplayasignificantlysmallerrolethanprivatetransfersdo.

ThisreportdoesnotaimtoprovidedetailedrecommendationsastohowpovertycanbeeradicatedinPeru.Whilestrategiestoreducepovertyarenecessaryandimportant,theydocarrytheriskofoversimplifyingaverycomplexanddifficulttask.InPeru,withabouthalfofthepopulationinpoverty,povertyeradicationwilltakealongtimeandrequirethecoordinatedeffortsofallpartsofsociety-thepublic,private,andvoluntarysectors-andtheinternationalcommunity.

Thereportdoeshold,however,thatamuchbiggerimpactcouldbeachievedwithavailableresources.First,economicandsocialpolicymakingwouldneedtobemorecloselyintegrated,informedbysoundtechnicalanalysesandadvice.Today,themanysocialpolicyprogramsoperateindependently;theytrytoreachtheirbeneficiarieswithdifferentmeansandlackstringentevaluation.Second,andcloselylinkedtotheabove,pro-poorpolicyformulationneedstobeaccompaniedbythoroughandgoodevaluation.Thisgoesbeyondtheneedfortargetingandprioritization.Itincludes,forpolicymakers,theabilitytoassesswhethercertaininterventionsdidindeedhelpornot.Italsoimpliesthatpolicymakersandtechniciansareabletoassesshowchangesinprogramnatureandhowchangesinexpendituresaredistributedandwhateffectthesechangeshave.Third,centralcoordinationpromisestobeeffectiveifitgoeshandinhandwithdecentralizedexecution,involvingotherpartnersinthefightagainstpoverty.ExamplesfromotherLatinAmericancountriesshowthatprivate-voluntary-publicpartnershipsinpovertyreductionatthelocallevelcanbeextremelysuccessful.

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AcknowledgmentsThisreportisaproductofthePeruCountryDepartment,LatinAmericaandtheCaribbeanRegionoftheWorldBank.JeskoHentschelledtheteamthatpreparedthereport.TheteamincludedAlbertoChong(paneldataanalysis),EdgardRodriguez(inequalityanalysis),andVajeeraDorabawila(consumptiondefinition,profile,andsimulations).ItalsodrawsonbackgroundpapersbyRafaelCortez(healthandnutrition),LuciaFort(indigenouspeopleandgender)andJaimeSaavedra(labormarketandeducation).JuanDiazprovidedvaluablesupport.ThedirectorofthePerucountrydepartment,IsabelGuerrero,andtheleadeconomist,ErnestoMay,providedoverallguidanceduringthepreparationofthereport.

ThanksareduetomanycommentatorsandadvisorsinPeru,theWorldBankandotherinternationalorganizations,amongthemJavierAbugattas,KatherineBain,ElenaConterno,DanielCotlear,FritzDuBois,WillemvanEeghen,JavierEscobal,AdrianFajardo,RosaFlores,PedroFrancke,CarolGraham,NormanHicks,DanielHinze,FredLevy,GilbertoMoncada,HelenaRibe,MarcosRobles,JoseAntonioRodriguez,NorbertSchady,MoisesVentocilla,RichardWebb,KinBingWu,andGabrielOrtizdeZeballos.ManythanksalsotoDeborahDavis,whoeditedthereport,andtoMargaritaCaro,whoproducedthefinaldocument.

Wewouldliketoacknowledgeclosecooperation,fruitfuldiscussions,andthegeneroussharingofdatainformationwithboththeInstitutoCuántoandthePeruvianStatisticalInstitute(InstitutoNacionaldeEstadisticaeInformación,INEI).Muchofthematerialandstatisticspresentedinthisreportarebasedonfourdifferenthouseholdsurveys.TwoofthemareLivingStandardMeasurementSurveys(LSMS)bytheindependentInstitutoCuánto(EncuestaNacionaldeHogares

SobreNivelesdeVida,ENNIV1994and1997);oneisanationalhouseholdsurveybytheNationalStatisticalInstituteINEI(EncuestaNacionaldeHogares,ENAHO1996);andoneisasurveyonviolence(EncuestadeHogaressobreViolencia,ENHOVI1997)bythesameinstitute.

Wewelcomecommentsonthereport.Pleasecommunicatesuchcomments,orrequestsforthestatisticalprogramsused,toJHentschel@worldbank.org.

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Peru-PobrezaYDesarrolloSocial,19941997ResumenDelInformeEsteinformecontienelaevaluacióndelprogresosocialenelPerúentre1994y1997.Engeneral,laevaluaciónpresentaaspectospositivosperotambiénsubrayavarioselementospreocupantes.Labuenanoticialaconstituyelamejoradelbienestarsocialenlosúltimosaños,lacualseverificaatravésdedistintosindicadores.Latasadepobreza-elporcentajedelapoblacióncuyogastototalnocubreelcostodeunacanastabásicadeconsumo-disminuyóenvariospuntosporcentualesyseencontróen49porcientoen1997.Consecuentemente,casi12millonesdeperuanoseranconsideradospobres.Lapobrezaextrema-aquelloshogarescuyogastonologracubrirunacanastabásicaalimenticia-,porotrolado,tambiéndescendiódeaproximadamente19a15porciento.Sinembargo,quedabantresymediomillonesdeperuanosenunagravesituacióndehambreynecesidad.Laasistenciaescolarseelevóligeramente,latasadealfabetismotuvounligeroincrementode87a90porcientoylapoblacióngozódemejoresnivelesdesaluden1997.Lomásimportanteenesteúltimoaspectoesquedisminuyólatasadedesnutricióninfantilenniñosmenoresdecincoaños.En1997,aproximadamente600,000niñosmenoresdecincoaños-unodecadacuatro-sufríandedesnutrición.ElCuadro1muestralaevolucióndediversosindicadoresdeniveldevida.

Cuadro1:IndicadoresBásicos1Cambio2 Nacional Urbana Rural

1994 1997 1994 1997 1994 1997Tasadedesnutrición(%) 30.0 23.8 17.4 12.2 44.7 37.3Tasadealfabetismo(%) 87.6 90.2 92.3 94.3 77.4 82.1Tasadepobreza(%) 53.5 49.0 46.1 40.4 67.0 64.7Brechadepobreza(%) 18.9 16.0 14.4 11.8 27.1 23.5

Tasadepobrezaextrema(%)

18.8 14.8 12.9 9.3 29.5 24.5

Desigualdaddeingresos,Gini

X .469 .484 .437 .441 .494 .500

Trabajodemenores(%) X 7.8 11.8 3.9 6.9 22.5 33.5Matrículaescolar('000) 4,8805,0802,9603,0301,9202,050Atenciónambulatoriapública(4semanas,miles)

1,7602,9901,2502,160 510 830

Conex.servicioseléctricos(%)

68.8 73.7 93.7 97.4 23.2 30.3

Conex.serviciossanitarios(%)

48.2 58.6 73.4 84.3 2.4 11.6

Redpúblicadeagua(%) 65.0 72.8 84.9 89.0 28.8 43.1Viviendasconpisodetierra(%)

X 41.0 43.3 20.4 23.2 77.9 79.6

1Ladefinicióndelosindicadoresseconsignaseconsignaalfinaldeestasección.2Elsímbolo' 'significauncambiopositivo,talcomolabajadelatasadepobreza.Elsímbolo'X'significauncambionegative.Fuente:EstimadosbasadosenENNIV(1994,1997)

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Estasmejorassedeben,sinlugaradudas,alfavorableentornoeconómicogeneralentre1994y1997,contasasrealesdecrecimientopercápitadeaproximadamente3.5porciento.Estecrecimiento,contrariamentealacreenciapública,sígeneróempleo.LaEncuestaNacionaldeHogaresSobreMedicióndeNivelesdeVida(ENNIV,InstitutoCuánto1994y1997)permiteestimarquesecrearoncercade1.3millonesdepuestosdetrabajoadicionalesenelmercadonacional,absorbiendotantoelaumentopoblacionalcomounatasamásaltadeparticipacióndelafuerzalaboral.Sinembargo,muchosdeestosnuevospuestosdetrabajofueronempleosinformales,demodoquelostrabajadorescarecendecontratosdetrabajoformales,segurodepensionesodesalud.EnelPerú,elemploinformal1esmuyextenso,encontrándosedesdehacetiempoenunnivelmásomenosconstantedeaproximadamente45porcientodelempleourbano,ysiendoaúnmayorenlaszonasrurales.Lastendenciaspositivasdelbienestarsocial,observadasenelCuadro1,sedebentambiénaesfuerzosimportantesdelgobiernopormejorarlascondicionesdevida.Entre1994y1997,másdemediomillóndefamiliassebeneficiarónconconexionesdeluzyagua;elsectordesaludpúblicabrindóatenciónamásdeunmillónadicionaldepacientesambulatoriospormes;yelnúmerodeniñosqueaststenalaescuelaaumentóen200,000.

Sedebemencionar,sinembargo,queexistenaspectospreocupantes,muchosdeellosestaníntimamenteligadosentresí.Elcrecimientoeconómicoylosprogramasgubernamentalesnohanllegadoatodosporigual.Enprimerlugar,lasdesigualdadesregionaleshanaumentado.Mientrasalgunasregionesmuestrangrandesavances,especialmenteLima,otrasregionesmuestranpocoprogreso,especialmentelaszonasruralesandinas.ElCuadro2esunamuestradelgradodedifferenciaporáreageográficaquesedaenlosavancesrealizadosentre1994y1997.Enlazonaruraldelasierra,lapobrezageneralpermaneceestancadaaúncuandoelgradodeseveridadhaya

disminuido.Deltotaldelareduccióndelapobreza,casi80porcientoprovienesólodedosregiones:Limaylaregióndesierraurbana.Encomparacionesinternacionales,Perúpermaneceentreaquellospaísesquetienenunavariaciónextremadamentealtadeniveldeingresoregional.

Cuadro2:GradodeAvancesdeMejorasenIndicadoresenComparaciónalPromedioNacional,19941997

Pobreza PobrezaExtrema DesnutriciónLimaCostaUrbana X XCostaRural X XSierraUrbanaSierraRural X X XSelvaUrbana XSelvaRural X1Elsímbolo' 'significaundesarollomejorqueelpromediodelpaís;elsímbolo'X'significaundesarollopeorqueelpromediodelpaís.Fuente:EstimadosbasadosenENNIV19941997.

1Ladefinicióndeinformalidadutilizadaenesteestudioseconsignaalfinaldeestasección.

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Ensegundolugar,elestudioencuentratambiénevidenciadequeladesigualdadaumentóentre1994y1997.Otrosestudios2hanseñaladoquedurantelasúltimasdécadasladesigualdadhavenidoreduciéndoseenelPerúhastamediadosdelosnoventademanerasostenida,graciasalmayoraccesoaactivosclavescomotierrayeducación.Enesesentido,elpequeñoaumentoenladesigualdadqueseregistraentre1994y1997,alconsiderarvariosmétodosdemedicióndeladistribucióndelingresoylariqueza,implicaríaunareversióndeunatendenciapositivahaciaunamayorequidadenelpaís.Porello,estefenómenodebeserobservadomuydecercaporlosencargadosdediseñarlaspolíticassocialesenelpaís.Lainequidadtieneademásefectossocio-económicosimportantes.Losestudiosrecienteshandemostradoquecuántomayoresladesigualdadsocial,mayorestambiénlatendenciaalaviolencia.Asimismo,elprogresoeconómicotambiénseveafectado,pueslassociedadesmasdesigualesostentanbajosnivelesdecrecimiento.

Elestudioencuentradosfactoresdetrásdeestosaumentosenladesigualdad:enprimerlugar,lamejoraeconómicaactualhabeneficiadomayormentealosperuanosconmejorniveleducativofrentealosquerecibieronmenoseducación.Esteesunpatrónquelaglobalizaciónyelcambiotecnológicoreforzarán,porloqueresultaprioritarioenfatizarlainversióneneducación.Ensegundolugar,eldesarrolloregionalhavariadonotablemente.Estadifferenciaeneldesarrolloregionalsereflejatambiénenladistribucióndelasprincipalesinversionespúblicas:mientrasqueelgobiernosehaesforzadoenllegarmásalapoblaciónmarginaldelaszonasrurales,esteesfuerzosehatraducidosóloenformaparcialenbeneficiosperceptibles.Aproximadamenteel70porcientodelosgrandeslogroseneducación,saludeinfraestructurasehandadoenlasciudades(Cuadro3).

Cuadro3:DistribucióndelNuevoAccesoaServicios

BásicosySociales,19941997(Porcentaje)Urbano Rural (Total)

Agua 57 43 (100)Electricidad 72 28 (100)Saneamiento 78 22 (100)SaludAmbulatoria 74 26 (100)Educación,matrícula 33 67 (100)Fuente:EstimadosbasadosenENNIV1994,1997

Entercerlugar,entre1994y1997eldesarrolloenelPerúfueinclusivoparamuchos,peroexclusivoparaotros.Existenaquítambiénaspectospositivos,comoquelasdiferenciasdegénerodisminuyeronyquealgunosgruposvulnerablescomolosconformadosporlosmigrantes3olosquenoposeentierras,compartenlosbeneficiosdeldesarrollo.Noobstante,otrosgruposaparentementequedanalazaga.Enestesegundobloqueelestudioidentificaclaramentealospueblosindígenas4,delosquesuintegraciónsocialypolíticatodavíaestamuylejosdesercalnzada.Económicamente,lospueblosnativoshansufridounretrocesoimportante:mientrasqueen1994unafamiliaindígenateníacuarentaporcientomásdeposibilidadesdeserpobrequeunafamilianoindígena,en1997eseporcentajesehaelevadoa

2Escobal,Javier,MáximoToreroyJaimeSaavedra.Losactivosdelospobres.CuadernosdeTrabajo.GrupodeAnálisisparaelDesarrollo.Grade.Lima..Diciembre1998.3Ladefiniciónoperativadeestacategoríaseincluyealfinaldeestasección.4Ladefiniciónoperativadeestacategoriaseincluyealfinaldeestasección.

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casicincuentaporciento(Cuadro4).Elestudioidentifica,alobservaraestasmismasfamiliasentre1994y1997,quesusituaciónnohaevolucionadotanfavorablementeenrelaciónalresto,aúnteniendoencuentasubajoniveldeeducación,elreducidoaccesoalosserviciosyalapropiedaddetierrasoviviendas.Lograrelprogresodelosindígenaspobresesunretomáscomplejoqueeldelospobresurbanos,cuyaintegraciónalosmercadosesmássencilladelograr,loqueimplicalanecesidaddeunesfuerzoespecial.

Cuadro4:$iques;MayoroMenorProbabilidaddeserPobre?ProporcionesRelativesdePobrezaentre

Grupos(Porciento)Nacional1994 1997

Indígenas(vernáculohablantes) +40.2 +48.7Infantes(05años) +26.0 +27.0niños(614años) +24.5 +25.5jóvenes,(1517años) +5.5 +8.6Familiasruralessintierras +3.4 -4.0Familiasruralesdirigidasporviudos -5.0 -14.2Familiasdirigidaspormujeres -12.8 -16.5Migrantes -16.0 -18.0Fuente:EstimadosbasadosenENNIV.ElCuadroregistraelriesgorelativodeserpobre,esdecir,elriesgoabsolutodeserpobreencomparaciónconotrosgrupos.Elsignopositivosignificaqueestegrupotienemayorproporcióndepobresqueelrestodelapoblación;elsímbolonegativoindicalocontrario.

Lasituaciónsocialdelaniñezcontinúasiendodificil.Dadalamayorfecundidaddelasfamiliaspobres,laproblemáticadelapobrezaestáestrechamentevinculadaalapoblacióninfantil.Lastasasdepobrezaqueprevalecenentrelosmásjóvenesdelasociedadperuana

continúandentrodeunrangomayoracualquierotrogrupodeedad.Yaúncuandolastasasdepobrezahayandisminuido,lareducciónesleveymuchomenordeloquefueparaotrosgrupos.Losdatosdelaencuestamuestrantambiénelproblemadeltrabajodemenoresporcuantocadavezesmayorelnúmerodemenorescuyasedadesfluctúanentre6y14añosquedebentrabajarparacontribuiralsostenimientofamiliar.Entre1994y1997haaumentadoelnúmerodemenoresdeedadquetrabajanmásde15horassemanalesen241mil.Diversosestudioshanseñaladoelimpactonegativoqueeltrabajodemenorespuedetenersobrelaeducación,comprometiendoelfuturodeestosniños.Enelcasodelosjóvenesqueyaestánenedaddetrabajar,elestudioseñalaqueeldesempleojuveniltienecifrasmuyaltas:18porcientoparalasmujeresy14porcientoparaloshombresenLima(1996),conunatendenciacreciente.

QuéesloQueAyudaalProgresodeunHogar?

Lafinalidaddelinformenoesdescribirlasituacióndelospobresdentrodelasociedadperuananibosquejarun''perfildepobreza"sobrelabasedelaúltimainformacióndisponible.Existenyamuchosestudiossobreello.Másbien,elestudiobuscaevaluaraquellosfactoresquedeterminanquelasfamiliasprogresenoquedenrezagadaseneltiempo,mediantelacomparacióndelosresultadosdelasencuestasde1994y1997.Estaevaluaciónesdeespecialimportanciaparalosresponsablesdediseñarlaspolíticaspertinentes.Porejemplo,unavisión

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estáticapodríarevelarqueelempleoinformaltienefuertecorrelaciónconlapobreza.Encambio,unavisióndinámicapuedeirmásallá,alrespondersilasfamiliasvinculadaspredominantementealmercadoinformaltienenmayoromenorprobabilidadrelativadesalirdelapobreza.

Atravésdeltiempohanhabidovariosfactoresquehaninfluidotantoenformapositivacomonegativaenelbienestardeloshogares.Losresultadosmásdestacablessonlossiguientes:

Loshogarescuyosingresosproveníandelsectorinformalhanprogresadomásquelosdelsectorformal.Estoesciertotantoenzonasurbanascomoenelcasodelempleoinformalfueradelcampoenzonasrurales.

Loshogaresmásnumerososnohanprogresadoalmismogradodeaquéllosmenosnumerosos.

Unamayoreducaciónimplicaunprogresomásrápido.

Elaccesoaservicioscomoalcréditoeinfraestructurabásicanosolamenterepresentaunaayudainmediata,sinoqueayudaaprogresarmásrápidamenteenformasnoconectadasdirectamentecondichoacceso.Elestudioencuentraevidenciamuyclararespectodelaimportanciaquerepresentaelaccesoavariosservicios:brindarserviciosenformaconjuntagenerasinergias.

Elinformetambiénincluyealgunosresultadosrespectoalaincidenciaeimpactoquetienelaviolenciasobrelasfamiliaspobresurbanas.Laviolenciaesunadelaspreocupacionesprincipalesdelospobresurbanos.Lastasasdeincidenciadevariostiposdeviolenciadifierendeacuerdoalgrupodepobreza,estandolospobresdoblementeexpuestosalaagresiónfisicaqueaquelloscuyaposiciónesmejordentrodelasociedad.Consecuentemente,susentidodeinseguridadesmayor.

PerspectivasParalaReduccióndelaPobrezaCrecimientoyEmpleo

UnadelasmayorespreocupacionesdentrodeldebatepúblicoenelPerúesestablecersielcrecimientohacreadoempleosysiestohaservidoparareducirlapobreza.Larespuestaesafirmativa.Elcrecimientoenlosañospasadosciertamentehacreadoempleos:aproximadamente1.3millonesmásdepersonashantenidoempleoremuneradoen1997queen1994.Lamayorpartedelospuestosdetrabajotuvieronsuorigenenelsectorinformal,peroellonoimplicaqueestuvieranmalremunerados.Latendenciaquepreocupaesquelaproductividadenlazonaurbananopareceaumentary,consecuentemente,lossalariosrealesenelmejordeloscasossemantienenconstantes.

Enprincipio,elpatróndecrecimientoenelPerúdebierahaberfavorecidoalospobres,porquelossectoresdondelostrabajadoresysusdependientestiendenmayormenteaserpobres(construcción,comercioyagricultura)hansidolosquecrecieronmásrápidamente.Aparentementeestohaservidoparaayudaralospobresenelramodeconstrucciónycomercio,peronotantoenelsectoragrícola,dondelareduccióndelapobrezahasidomenos

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rápidadeloqueseesperaba.Elcrecimientoenelagronohageneradomayorimpactoencuantoaempleo.Estoposiblementesehayadebidoaquedichocrecimientoapenashayarevertidoel"retrocesoenlaproductividad"quesediocomoresultadodelarecesiónexistenteenlaagriculturaacomienzosdeladécada.Elloimplicaqueelposteriorcrecimientodelaagriculturahaconducidoarecuperarnivelesdetrabajomásintenso,esdecirhorariosmáslargosportrabajador,peronomásempleo.

VariassimulacionesdemuestranlaimportanciadelcrecimientoenrelaciónconlareduccióndelapobrezaenelPerú.Sibienlassimulacionessonsencillas,permitenmostrarqueeltipodecrecimientoysudistribuciónregionalesimportanteparaelimpactosobrelapobreza.Sielcrecimientoestábasadomayormenteenlaagricultura,construcciónycomercio,ysuimpactosereflejamayormenteenlaszonasrurales,lareduccióndelapobrezaserámayorenelcortoplazo.Esporelloquedebecuidarsequelaspolíticasnoseandiscriminatoriasencontradedichossectores.

ElGastoSocialylaLuchaContralaPobreza

Esimportanteanalizarladistribucióndelgastosocialysupapelenlaluchacontralapobreza.Alexaminarlaincidenciadeunos7.6milmillonesdesolesdestinadosporelgobiernoen1996paraestosfines(cercade40porcientodeltotaldelpresupuestodelgastopúblico),sepuedeverqueésteestáligeramenteorientadohacialaspersonasdemejorsituacióndentrodelasociedadperuana.Elloquieredecirquelosmáspobresobtienenmenosdeestosgastosqueladistribuciónquelescorresponderíaenrelaciónasupesoenlapoblación(Cuadro5).Estosedebeengranparteaquelosgastoseneducaciónsuperioryatenciónhospitalariaestánsesgadosencontradelospobres,entreotros.

Cuadro5:DistributionAgregadadeGastosSociales,1996

Quintil Proporcióndelgastototal1(losmáspobres) 16.62 18.63 21.24 22.45(losmásricos) 21.1(Incluyeeducación,salud,programasdeluchacontralapobrezayvivienda)Fuente:EstimadosbasadosenENAHO1996yPresupuestoPúblico1996.

Variosdelosprogramasgubernamentalesespecializadoslleganamuypocosdelospobresylastransferenciasdirectasdefondospúblicostienenunpapelnotablementemenoraldelastransferenciasdelsectorprivado,incluyendoenéstaslastransferenciasendinerooespeciesdefamiliares,amigos,organizacionesreligiosas,voluntarias,etc.ElprogramadealimentosPRONAAyelfondosocialFONCODESsonlosprogramasquetienenmayorcoberturaymenorestasasdeescape(mejorfocalización),perolosprogramasdecréditoparavivienda,asícomolosdeinfraestructuradeCOOPOP,FONAVIeINFESllegaronsolamenteaunoscuantosdelospobresen1996.LaayudaalimentariatieneelmayorefectopositiveenlaszonasruralesdelPerú.Sinembargo,enelpaíslastransferenciasdefondosprivadostienen,porlogeneralunpapelsignificativamentemásimportantequelastransferenciasdefondosdelsectorpúblico.

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DelasEstrategiasSectorialesaunEnfoqueAmplioyConsistenteParaCombatirlaPobreza

ElinformenopretendeofrecerrecomendacionesdetalladassobrelaformacómosepuedeerradicarlapobrezaenelPerú.Suobjetivoesproporcionarunarápidaretroalimentaciónsobrelosdesarrollossocialesylapobreza,segúnlaúltimaEncuestaNacionaldeHogaresSobreMedicióndeNivelesdeVidapublicadaporInstitutoCuántoenJuniode1998,combinandodichainformaciónconunanálisisdepolíticaspertinentessobrepatronesdecrecimientoyladistribucióndelosgastossociales.Cabeseñalarquesibienlasestrategiasglobalesparareducirlapobrezasonnecesarias,noconstituyenunremedioinmediatoparaunproblematancomplejodesuperarcomoeldelapobreza.EnelPerú,dondecasilamitaddesupoblaciónestáconstituidaporpobres,laerradicacióndelapobrezatomarámuchotiempoyserequieredelesfuerzocoordinadodetodalasociedadelsectorpúblico,elsectorprivadoylasorganizacionesvoluntarias,aligualqueeldelacomunidadinternacional.

Elinformetampocorecomiendalacreacióndenuevosprogramasomodificacionesalosprogramasactuales.Enlíneasgenerales,losprogramasdeluchacontralapobrezaenelPerúponenénfasisenlossectorescorrectos,alincluirayudadeemergenciaconenfoquenutricionalyinfraestructurabásica.Sinembargo,elestudiorevelaquepodríalograrseunimpactomuchomayorconlosfondosdisponibles:

Primeramente,eldiseñodelaspolíticassocialesyeconómicasnecesitaríanestarmejorintegrados,asícomobasadosenmayorniveldeanálisisyasesoría.Actualmente,ungrannúmerodeprogramasdepolíticasocialoperaenformaindependiente,tratandodellegaralosbeneficiariosatravésdediferentesmediosycarecedeunaevaluaciónestricta.SolamenteenelMinisteriodelaPresidenciaexistenseisprogramasenelsectoreducaciónindependientesyadicionalesalos

delMinisteriodeEducación-.LosprogramasdenutriciónsonmuchosylosadministranlosMinisteriosdeFinanzas(VasodeLeche),dePromocióndelaMujeryDesarrolloHumano(PRONAA),deSalud(ProgramadeSaludBásica,PACFO)deEducaciónydelaPresidencia(FONCODES).Losgastosdemuchosdeestosprogramas,aunqueciertamentebienintencionados,nolleganalosmáspobresdelasociedadyamenudoestánaisladosentresí.Actualmenteseutilizadiversosmecanismosparafocalizarlasaccionesdelosprogramaspúblicos,sinqueexistaconcordanciaentreellos.Todoloanteriorseñalaquesepodríalograrunamayorreduccióndelapobrezasilasintervencionesfuesenintegradas,esdecirsisebrindanenformaconjuntaycoordinada.EnPerú,existenactualmentedecretosantagónicosquedanpodertantoalMinisteriodelaPresidenciacomoalConsejodeCoordinaciónSocialCIASenestecampo,aunqueningunadelasinstitucionestieneverdaderopoder.SibienelCIAShareiniciadorecientementesusesfuerzos,serequiereunpotenciamientodelasaccionesdecoordinación,talvezmediantelaintegracióndelosministeriossocialesenunconsejomuchomáspoderosoparalaelaboracióndepolíticasenestecampo.

Ensegundolugar,eíntimamenteligadoaloanterior,laformulacióndepolíticasenfavordelospobresrequieremejoresymáscompletossistemasdeevaluación.Estovamásalládelanecesidaddefijarobjetivosyprioridades.Losdiseñadoresdelaspolíticasdebenpoderevaluarsideterminadasintervencionesfuerononodeutilidad.Elloimplicaquesepuedaevaluarlaformacómosellevaacaboladistribuciónycúaleselefectodeloscambios,tantoenlanaturalezadelosprogramascomoenlosgastos.

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Entercerlugar,lacoordinacióncentralprometeserefectivasivadelamanoconlaejecucióndescentralizada,involucrandoaotrossociosenlaluchacontralapobreza.LosejemplosquebrindanotrospaísesdeAméricaLatinamuestrancómolaasociaciónentreorganismosprivados-voluntariosypúblicospuedetenermuchoéxitoenlareduccióndelapobrezaanivellocal.Unadelasrazonesparaeléxitodeestasasociacionesesquecadaunadelasorganizacionescontribuyeconsupropiaventajacomparativa.Elgobiernocentralponeelapoyofinancieroylaorganización,elgobiernomunicipalelconocimientodelámbitolocal,ylasorganizacionesvoluntariasonogubernamentalesyorganizacionesdebasecontribuyenamenudoconunacomprensiónampliaydirectadelosproblemasdelospobres.

Definiciones

Atenciónambulatoriapública:

Númerodeatencionesambulatorias(enmiles)por(4semanas,miles)lareddesaludpúblicaenunperíododecuatrosemanas.

Brechadepobreza(%):

Diferenciaentreelgastopromediodelospobresylalíneadepobreza,expresadacomoporcentajedelalíneadepobreza.

CoeficientedeGini:

Indicadorutilizadopararepresentarelgradodedesigualdadenladistribucióndelingreso.

Conexióndeservicioseléctricos(%):

Porcentajedelapoblaciónconconexiónasistemapúblicodeelectricidad.

Conexióndeserviciossanitarios

Porcentajedelapoblaciónconconexiónasistemapúblicodedesagüe.

(%):

Desigualdaddeingresos,Gini:

Lavariableingresoconsideralosingresosprovenientesdelautoempleo,salarios,transferenciasyrentasdepropiedades.

ENAHO: EncuestaNacionaldeHogaresrealizadaporelInstitutoNacionaldeEstadísticaeInformática(INEI).Hasidorealizadasemestralmentedesde1995.

ENNIV: EncuestaNacionaldeHogaressobreMedicióndeNivelesdeVida,realizadaporelInstitutoCuántodirigidaamedirlasituaciónsocialyeconómicadelaspersonas.Hasidorealizadaen1991,1994y1997.

Informalidad:Referidaalasactividadesdeempleoyautoempleonosujetasalpagodeimpuestos,

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seguro(IPSS),sinfirmadecontratos,sinderechosavacacionesnisindicatos.

Indígenas: Paraefectosdelpresenteinformeseentiendecomofamiliaindígenaatodaaquellafamiliacuyajefedicequesulenguamaternaseaelquechua,aymara,campauotralenguanativa.Estavariable"lenguanativa"hasidoutilizadacomoproxydeetnicidad,dadoqueapartedelalenguaseentiendequelasfamiliasindígenascompartenademástradiciones,vestimenta,creencias,etc.

Matrículaescolar('000):

Númerototaldematriculadosenprimariaysecundaria.

Migrantes: Hogarescuyojefemencionóquenohabernacidoenlalocalidad(pueblo,localidadderesidenciaactual).

Redpúblicadeagua(%):

Porcentajedelapoblaciónconconexiónasistemapúblicodeagua.

Tasadealfabetismo(%):

Porcentajedelapoblaciónporencimadelos6añosdeedadquesabeleeryescribir.

Tasadedesnutrición(%):

Porcentajedeniñosmenoresdecincoañosconunadesviaciónestándardetallamayorados,pordebajodelanormainternacionalajustadacorrespondienteasuedad.

Tasadepobreza(%):

Porcentajedelapoblaciónincapazdecubrirelcostodeunacanastabásicadeconsumo.Alvalordeestacanastadeconsumotambiénseledenominalíneade

pobreza.

Tasadepobrezaextrema(%)

Porcentajedelapoblacióncuyogastonologracubrirunacanastamuyaustera.

Trabajodemenores(%):

Porcentajedetodoslosniños,de6a14añosdeedad,quetrabajanmásde15horassemanales.

Viviendasconpisodetierra(%):

Porcentajedelapoblaciónqueresideenviviendasconpisodetierra.

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1.Overview

PovertyandSocialDevelopments,19941997

ThisreportevaluatessocialprogressinPerufrom1994to1997.Itcarriesmainlygoodnewsbutalsoreportsseveralworrisomedevelopments.Thegoodnewsisthatsocialwelfareimprovedoverthethreeyears-andthisistruewhenlookedatfromavarietyofangles.Thepovertyrate,thepercentageofthepopulationnotabletofinanceabasicbasketofgoods,hasdeclinedbyseveralpercentagepointsandnowstandsat49percent-roughly12millionPeruviansarethereforeconsideredpoor.Severeconsumptionpoverty-anextremelyausteremeasure-hasalsodeclined,fromabout19to15percent.Thisdoes,nevertheless,leavethreeandahalfmillionPeruviansintheimmediatedangerofhungeranddeprivation.Inlinewithconsumptionpovertyrates,schoolattendancehasrisenslightly,literacyratesincreasedfrom87to90percent,andthepopulationishealthier.Mostimportantamongthelatter,therateofmalnutritionforchildrenbelowtheageoffivehasfurtherdeclined.About600,000childrenyoungerthanfive,oroneineveryfour,weremalnourishedin1997.

Theseimprovementsarewithoutdoubtduetothefavorableoveralleconomicenvironment,withpercapitarealgrowthratesfrom1994to1997atabout3.5percent.Thisgrowth,contrarytopublicbelief,didcreatejobs.Weestimatethatabout1.3millionadditionaljobswerecreatedintheeconomy,absorbingbothapopulationincreaseandahigherparticipationrateinthelaborforce.Manyofthesenewjobsareinformaljobs,however,soworkersarewithoutformalcontracts,pensioninsurance,orhealthinsurance.InformalityinPeruremainsat

aconstantrateofabout45percentofurbanemployment,evenhigherinruralareas.ThepositivesocialwelfaretrendsarealsoduetosubstantialGovernmentefforts:from1994to1997,morethanhalfamillionhouseholdsreceivedwater,electricity,andsanitationconnections;thepublichealthsectorattendedmorethanonemillionadditionalambulatorypatientspermonth;and200,000morechildrenwereinschoolin1997comparedto1994.

Buttherearealsosomeworrisomedevelopmentstoreport-andmostofthemarecloselyknittogether.EconomicgrowthandGovernmentprogramshavenotbeenspreadequallyandhavenotbenefitedeverybody.First,regionaldisparitieshavegrown,withsomeregionsshowingenormousprogress,especiallyLima,andotherregionsfallingrelativelybehind,especiallytheruralareasinthehighlands.IntheruralSierra,overallpovertyremainsstagnantwhileitsseverityhasdeclined.Ofthetotalreductioninpoverty,almost80percentstemmedfromtworegionsalone:LimaandtheurbanSierra.IninternationalcomparisonsPeruremainsoneofthecountrieswithanextremelyhighvariationofregionalincome.

Second,withregionaldisparitiesincreasingwealsofindsomeevidencethatinequalityhasriseninthethreeyearsunderstudy-asmallincreaseininequalitycanbeobservedwhenusingseveralmeasurementmethodsandwhenlookingatthedistributionofincomeorwealthalike.Thisincreaseininequalitycomesafteradecreaseoveralongtimeperiodfrom1985to1994.Andalthoughitisnotatallcertainthatinequalitywillcontinuetorise,policymakersshouldcloselywatchit.Evidencenowexiststhatmoreunequalsocietiestendtobemoreviolentsocieties.Economicprogressalsodependsonequality,withmoreunequalsocietiesshowingaworsegrowthrecord.And,clearly,inequalityandpovertyarealsodirectlylinked:

Page2

foranygivennationalincome,themoreunequalthesociety,thehigherthepovertyrate.WefindtwofactorsbehindtheseinequalityincreasesinPeru.ThemoreeducatedPeruviansprofitedmorefromthecurrentupswingthanthelesseducated.Obviously,thismeansthatimprovingthequalityofprimaryandsecondaryeducationwoulddecreaseinequality.Additionally,regionaldevelopmentvariedstronglyandcontributedtothesmallriseininequality.Thisdifferentregionaldevelopmentisalsomirroredinthedistributionofmajorpublicinvestments:Whilethegovernmenthasmadeanefforttoreachoutmoretothemarginalruralpopulation,thisefforthasonlypartiallytranslatedintomeasurablebenefits.Ofthelargeachievementsineducation,healthandinfrastructure,about70percenthavebeenincities.

Third,Peru'sdevelopmentinthepastyearshasbeeninclusiveformanybutexclusiveforothers.Whilewefindgenderdifferencesnarrowingandvulnerablegroupssuchasmigrantsandthelandlesssharingthebenefitsofdevelopment,certaingroupsappeartohavefallenfurtherbehindorremainhighlyatriskofdeprivation.Onegroupisclearlytheindigenouspopulation.Theirsocialandpoliticalintegrationisstillfarfromachieved.Andwenowfindthateveneconomicallythenativepopulationhasfallenfurtherbehind:whilein1994anindigenousfamilywas40percentmorelikelytobepoorthananon-nativefamily,in1997theywerealmost50percentmorelikelytobepoor.Additionally,observinghundredsofthesamefamiliesfrom1994to1997,theindigenousfamilieshaveclearlydoneworse,evenifwecontrolfortheirlowereducationaltraining,loweraccesstoservices,andlowerlandorhousingownershipcomparedtothenon-nativepopulation.

Thesocialsituationofchildrenremainsbleak.TheyoungestinPeruviansocietycontinuetohavefarhigherpovertyandseverepovertyratesthananyotheragegroup.Andalthoughpovertyrates

decreased,thedropwasslightandmuchlessthanforothergroups.Also,thesurveydatatellsasadstoryaboutchildlaborasmoreandmoreyoungstersbetweentheagesof6and14work.Inadditiontochildren,manyyoungadolescentsarenotfaringwellinPeruviansociety.Youthunemploymentisveryhigh,18percentforfemalesand14percentformalesinLimain1996,andshowsarisingtrend.Ininternationalcomparison,whilePerureducedinfantmortalityfrom54(1990)to42deathsper1,000livebirthsin1996,itisstilllaggingbehindtheregionalachievementsforcountriesofitsincomelevelanditplacesPeruamongtheworstintheLatinAmericanregion.

ThisreportdoesnotaimtodescribethesituationofthepoorinPeruviansociety-tosketcha"povertyprofile".Manyotherstudieshavedonethis.Rather,weareinterestedinassessingwhatdetermineswhetherfamiliesgetaheadorfallbehindovertime.Thisisofspecialrelevancetopolicymakers.Forexample,astaticviewmighttellusthatinformalemploymentisastrongcorrelateofpoverty.Butaviewovertimewillshowwhetherthedepthofpovertyincreasesifahouseholdislinkedpredominantlytotheinformalmarket.

WhatHelpsHouseholdsAdvance?

Anumberoffactorshaveinfluencedhouseholdwelfareovertime,inbothpositiveandnegativeways.First,surprisingly,householdsweremorelikelytoadvanceiftheirincomestemmedfromtheinformalsectorthanfromtheformalsector.Thisistrueinurbanareasaswellasininformaloff-farmemploymentinruralareas.Second,householdsizematters.

Page3

Largerfamilieshavedoneworsethansmalleronesthisrelationshipcanworkthroughhigherdependencyratiosthatcanlimittheabilityofhouseholdstosave.Third,moreeducationmeansfasteradvancement.Finally,savingsandaccesstobasicserviceslikewater,electricityorsanitationisnotonlyofimmediatesupporttohouseholdsbuthelpsthemadvancefasterinwaysnotjustdirectlyconnectedtoservicesaccess.Wealsofindthatbundlingofsuchservicesmatters:providingtwoservicesjointlyhasamorepositiveeffectthanthesumofprovidingeachoneseparately.

Thereportalsoincludessomefindingsabouttheincidenceandimpactofurbanviolenceonthefamiliesofthepoor.Whilewecannotlinkinsecuritydirectlytowelfaredevelopments,violenceisoneofthemainpreoccupationsoftheurbanpoor.Theincidenceofvarioustypesofviolencediffersbypovertygroup,thepoorbeingabouttwiceaslikelytobeexposedtophysicalaggressionasthebetter-offinsociety.Consequently,theirfeelingofinsecurityishigher.

ProspectsforPovertyReduction-GrowthandEmploymentLinks

OneofthebiggestconcernsinthePeruvianpublicdebateonpovertyiswhethergrowthhascreatedemploymentandwhetherthishasledtopovertyreduction.Wefindthatgrowthhasindeedcreatedemployment;about1.3millionmorepeoplehavebeeninremuneratedemploymentin1997comparedto1994.Themajorityofjobswerecreatedintheinformalsectorbuttheywerenotnecessarilylow-payingjobs.Aworrisometrendisthaturbanproductivitydoesnotseemtoberisingand,consequently,realwagesareflatatbest.

Onfacevalue,Peru'sgrowthpathoverthepastyearswaspro-poorbecausethesectorswhereworkersandtheirdependentsaremostlikelytobepoor(construction,commerceandagriculture)grewfastest.Thisappearstohavehelpedthepoorinconstructionand

commerce.Inagriculture,however,povertyreductionwasslowerthancouldhavebeenhopedfor.Employmentcreationasacorollarytoagriculturalgrowthwasnotstrong.Thiscouldbeduetoaproductivitybacklogstemmingfromtherecessionatthebeginningofthe1990s,implyingthatagriculturalgrowthfirstledtomoreintensivework,i.e.longerhoursperemployedperson.

AnumberofsimulationsshowhowimportantgrowthremainsforpovertyreductioninPeru.Thesimulationsareverysimpleand,forexample,donottakeintoaccountthatworkerswillmovebetweenareasandsectorsorthattheemploymenteffectofgrowthwilldifferbetweensectors.Thesimulationsdoshow,however,thatthetypeofgrowthanditsregionaldistributionwillmatter-themoregrowthisbasedinagriculture,constructionandcommerce,andthemoreitsimpactsfilterthroughtotheruralhighlandsandlowlands,themorepovertywillbereducedintheshortrun.Whilethegrowthpatternshouldnotbeartificiallytiltedtowardssuchsectors,investmentinthesesectorswilldependonacontinuationofnon-discriminationpolicies.

Page4

SocialExpenditure

Thedistributionofsocialandanti-povertyexpenditureshasbeendisappointing.Thedistributionof7.6billionsoles(about40percentofthetotalpublicbudgetin1996)ismildlytiltedtowardsthebetter-offinPeruviansociety;i.e.,thepoorestobtainlessoftheseexpendituresthantheirpopulationshare.Inlargepartthisisduetotheanti-poordistributionofhighereducationandhospitalexpenditures.

SeveralspecializedGovernmentprogramsreachonlyasmallproportionofthepooranddirectpublictransfersplayasignificantlysmallerrolethanprivatetransfersdo.ThenutritionprogramPRONAAandthesocialfundFONCODEShavethehighestcoverageandlowestleakageratesbutthehousingcreditprogramsaswellastheinfrastructureprogramsofCOOPOP,FONAVIandINFESreachedonlyfewofthepoor.FoodaidhasthelargestpositiveeffectinruralPeru,wheretheseverepovertyratewouldhavebeen3percenthigherhadtheseprogramsnotexistedin1997.However,privatetransfersgenerallyplayasignificantlymoreimportantrolethanpublictransfersintheruralandurbanareasalike.

FromIndividualSectorStrategiestoaConsistentandBroad-BasedAnti-PovertyFocus

ThereportdoesnotaimtoprovidedetailedrecommendationsastohowpovertycanbeeradicatedinPeru.Rather,itpresentsaquickfeedbackaboutsocialdevelopmentsandpovertybasedonthenewLivingStandardMeasurementdatafromtheInstitutoCuántoreleasedinJune1998,andonpolicy-relevantanalysisofgrowthpatternsandthedistributionofsocialexpenditures.Whilestrategiestoreducepovertyarenecessaryandimportant,theydocarrytheriskofoversimplifyingaverycomplexanddifficulttask.InPeru,withabouthalfofthepopulationinpoverty,povertyeradicationwilltakealong

timeandrequirethecoordinatedeffortsofallpartsofsociety-thepublic,private,andvoluntarysectors-andtheinternationalcommunity.

Thereportalsodoesnotrecommendthecreationofnewprograms,nordoesitmakeastatementabouttheappropriatesizeandmixofprograms.Inbroadlines,wefindthatthePeruviananti-povertyprogramswiththeirmixofemergencyhelp,nutritionalfocus,andinfrastructureemphasizetherightareas.However,webelievethatamuchbiggerimpactcouldbeachievedwithavailablefunds.

First,economicandsocialpolicymakingwouldneedtobemorecloselyintegrated,informedbysoundtechnicalanalysesandadvice.Today,themanysocialpolicyprogramsoperateindependently;theytrytoreachtheirbeneficiarieswithdifferentmeansandlackstringentevaluation.TheMinistryofthePresidencyalonehassixprogramsintheeducationsectoroutsideandinadditiontothoseoftheMinistryofEducation.NutritionprogramsareplentyandadministeredbytheministriesofFinance(VasodeLeche),WomenandHumanDevelopment(PRONAA),Health(BasicHealthProgram,PACFO),andEducationaswellastheMinistryofthePresidency(FONCODES).Expendituresofmanyoftheseprograms,althoughwellintended,donotreachthepoorestinsocietyandareoftenisolatedinnature.Manydifferentpovertymapsandtargetingmechanismsarecurrentlyemployed,andtheseneedtobeharmonized.Wefindthatpovertyisreducedmosteffectivelywhenifinterventions

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areintegrated,thatisprovidedjointlyandinacoordinatedway.InPeru,conflictingdecreesempoweringtheMinistryofthePresidencyandtheSocialCoordinationCouncil(CIAS)currentlyexistbutneitherinstitutionhastruepowerormanpower.Withoutintegratingsocialministriesintothemuchmorepowerfulcouncilforeconomicpolicymaking,weakcoordinationofsocialprogramsislikelytocontinue.

Second,andcloselylinkedtotheabove,pro-poorpolicyformulationneedstobeaccompaniedbythoroughandgoodevaluation.Thisgoesbeyondtheneedfortargetingandprioritization.Itincludes,forpolicymakers,theabilitytoassesswhethercertaininterventionsdidindeedhelpornot.Italsoimpliesthatpolicymakersandtechniciansareabletoassesshowchangesinprogramnatureandhowchangesinexpendituresaredistributedandwhateffectthesechangeshave.

Third,centralcoordinationpromisestobeeffectiveifitgoeshandinhandwithdecentralizedexecution,involvingotherpartnersinthefightagainstpoverty.ExamplesfromotherLatinAmericancountriesshowthatprivate-voluntary-publicpartnershipsinpovertyreductionatthelocallevelcanbeextremelysuccessful.Onereasonisthateachorganizationbringsitscomparativeadvantagetothetable:centralgovernmentbringsfinanceandorganization;municipalgovernmentbringslocalknowledge;andnon-governmentalorganizations(NGOs)oftenbringagoodanddirectunderstandingoftheproblemsofthepoor.Forthislatterpointthereporthassomeevidence:In1996,NGO-administeredprogramshadasignificantlybettertargetingrecordthanmostpublicprogramsandmatchedthegoodtargetingresultsofFONCODESandPRONAA.

Outline

Thisreportisstructuredasfollows.Section2containsaprecautionary

warning.Itisashortrecapofwhathouseholdsurveyscanandcannotdo,includinganassessmentofthereliabilityofpovertystatistics.Section3looksatnationalandregionalindicatorsofwell-beingbetween1994and1997,andatwhyinequalityrosebetweenthetwoyears.Section4presentsourfindingsastowhichgroupsinsocietydidanddidnotbenefitfromthegeneralriseinlivingstandardsinPeru.Further,weexaminewhichmainfactorsareresponsibleforsuchwelfarechanges.Section5examinestheprospectsforpovertyreduction,givenvariousgrowthratesoftheeconomy,differentassumptionsaboutinequalityand-mostimportantly-differenttypesofgrowthpatterns.Section6takesalookatthedistributionofsocialexpendituresin1996,i.e.,whichgroupswereandwerenotreachedbytheGovernment'slargesocialprograms.Section7describeskeyinstitutionalingredientsfordevelopingsuccessfulpovertyreductionstrategies.TheAnnexesofthisdocumentgivedetailedinformationondatasourcesanddefinitions,methodologies,andreportonanumberofrobustnesstestsoftheresults.

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2.PovertyRatesasPolicyGoals?MuchofthecurrentpoliticaldebateinPeruconcernswhetherpovertyrateshavefallenorrisenoverrecentyears.TheprominenceofpovertyratesinthepublicdebateispartlyduetotheGovernmenthavingsetcleargoalsofpovertyreduction.ItisalsopartlyduetoaheatedpublicdebateaboutsocialconditionsinPeru.Beforelaunchingintopovertymeasurement,profiles,andcorrelatesinthenextsection,webrieflywanttoargueinthissectionthat,yes,settingpovertyreductiongoalsisimportantandlaudable.However,estimatesofpovertyratesaremuchmorefragilethanoftenthought.Furthermore,liftingpeopleoutofpovertyhasamuchbroadermeaningthanraisingthemaboveapovertyline.

Povertyrateestimatesarebasedonhouseholdsurveys,whichareimportantandindispensabletoolsforpovertyanalysesandhencecrucialforpolicyformulation.Forexample,thegeographicaldistributionofpovertyandseverepovertyisaveryimportanttoolforexpendituretargeting.Householdsurveysareindispensableforanalyzingthedistributionandcoverageofpublicprograms-whichgroupsinsocietyobtainwhatfromthepublicpurse.Similarly,theycanservetotrackenrollmentrates,illnesspatterns,serviceaccess,andliteracyratesatrelativelymoderatecostbasedonpopulationsamplesandarethereforemuchlesscostlythanpopulationcensuses.Surveysalsohelptodeterminethecausesofpovertyandwell-being,aswellasthefactorsinfluencingmalnutritionandchildmortalityrates.StudiescoveringtheseandmanyothertopicshavebeenusedinpolicymakinginPeruformanyyears.

Butpovertyanalysisbasedonsuchsurveysis,byitsverynature,not

anexactscience.Thechoiceofpovertylinesandthedeterminationofconsumptionandincomedependonavastamountofassumptionswhich,ifchangedonlyslightly,canproducequitedifferentpovertyrates.Itis,therefore,notsurprisingthatdifferentsurveyswillproducedifferentpovertyrates,asisthecaseinPerurightnow.TheStatisticalInstituteINEIandInstitutoCuántohave,forexample,quitedifferentquestionnairestryingtocapturehouseholdfoodexpenditures.Withdifferentquestionsfordifferenttypesofproductsorproductcategories,itisonlylogicalthatestimatesofconsumptionandpovertywilldiffer.Thisdoesnotmeanthatoneismoreaccuratethantheotheris.Whetherpovertyis45,49,or53percentshould,intheend,notbeatthecenterofattention.However,whetherandtowhatdegreepovertyincreasedordecreased,usingaconsistentandcommonmethodologyisofimportancetopolicymakers.SomeoftheseaspectsarefurtherexploredinAnnex2.

Graph1:SeverePovertyRatesandTheirMarginsofErrors

Thefactthatpovertycalculationsarebasedonasampleofhouseholds,henceasubsetofthePeruvianpopulation,alsocarriesimplications.Samplesaredesignedtoreproducethewholepopulationbuttheycanneverbeasexactasinformationthatcoverseverybodyinthecountry.Hence,theycarryamarginoferror,asdopovertyratescalculatedfromthesesamplesurveys.Graph1showswhatthismarginoferrormeansinthecaseofPeru.Weusethe

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calculatedseverepovertyrateasanexample.5Thetwocolumnsindicatetherangeinwhichweareveryconfidentthatthetrueseverepovertyratelies.6Ascanbeseen,whileweestimatethatseverepovertyhasdroppedsubstantiallyfrom18.8to14.8percentbetween1994and1997,drawingsuchconfidenceintervalsaroundthemisquiterevealing.If,indeed,wewereatthelowerendoftheintervalin1994andattheupperendin1997,theratesforthetwoyearsmightactuallybeverysimilar.And,onthecontrary,ifthetrue1994ratewas20percentin1994andthetruevaluefor1998wasatthelowerend,around13percent,thedropinseverepovertycanactuallybebiggerthanweestimatehere.

Further,whileapolicyfocusonliftingpeopleoverthepovertylineislaudable,povertyhasobviouslyamuchbroadermeaning.Incomeorconsumptionareonlymeansofattainingbetterlives,andnotendsinthemselves.Lowermalnutritioninchildren,betterhealthofthepopulation,longerlives,lowermaternalandinfantmortalityrates,higherliteracy,lesshunger,moresafety,lessdiscriminationinworkandsociallife,andmoreactiveparticipationinpoliticalandsocialaffairsofcommunitiesandthecountrycharacterizebetterandlesspoorsocieties.Andseveraloftheseotherdimensionsmightnotbelinkedtoonlyconsumptionpoverty:crimeandviolencemighteffectlargepartsofthepopulation,discriminationinthejobmarketcanexistagainstcertaingroupsinsociety,orchildrenmightbemalnourishedalthoughtheygrowupinratheraffluenthouseholds.

Inconclusion,theanswertothequestionwhetherpovertyratesshouldbepolicygoalsisclearlyyes.Thiscommitspolicytoservingthemostmarginalizedgroupsinsociety.However,policymakersneedtobeawareoftheoftenquitefragilenatureofsuchpovertyestimates.Andfinally,reducingpovertyratesisonlyameanstohelpingpeoplelivehealthier,longerandbetterlives.

5Theseverepovertyratepresentedhereisnotstrictlycomparablewiththeextremepovertyrategenerallyreportedduetothespecificsofourconsumptiondefinition.SeeAnnex2ofthisreport.6Therangesindicatethatwecanbe95percentconfidentthatthetrueseverepovertyratesliewithintheupperandlowerboundsoftheinterval.

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3.Poverty,Inequality,andSocialDevelopments,19941997ThissectionprovidesbasicstatisticsonpovertyandsocialdevelopmentinPerusince1994.Ittakesacloseregionallookatwherethisprogresshasbeenfasterandwhereslowerandalsoassesseswhoinsocietyhasprofitedmostfrompublicinvestmentsinfiveareas:water,sanitation,electricity,education,andhealth.Finally,weexploretherecentincreaseininequalityandtraceittoitsunderlyingcauses.

BasicDevelopments

IndicatorsUsed.WeaimtolookatsocialprogressinPerufromanumberofdifferentangles.First,weuseoutcomeindicatorsofthedevelopmentofsociety-therateofchildrenbelowtheageoffivebeingmalnourishedandtheliteracyrateofthepopulation.7Secondarepovertyindicators.Throughoutthisreport,povertyisdefinedasastateinwhichtheaffectedpopulationhaspercapitaexpenditureslessthanneededtopurchaseaverybasicbasketoffoodandnon-foodgoods.Wheneverwetalkaboutpovertyinthisreportweemployconsumptionpercapitaasthewelfaremeasure.Thederivationofthecostofthebasicbasketofgoods(whichthencomprisesthepovertyline)issomewhatdifferentthangenerallyappliedinPeru.Especially,forcomparisonreasonsbetweenthetwohouseholdsurveyyears,1994and1997,wehadtomakeanumberofimportantbuttediousadjustments,asexplainedindetailinAnnex2ofthisreport.8Moreimportantthanthepercentageofthepopulationbelowthisimaginarylineishowfarthepoorareawayfromit.Forthisweusethepovertygaptomeasuretheresourcesnecessarytobringallindividualstothepovertyline.Thisisexpressedasaproportionofthepovertyline

itself.Wealsouseanadditional,muchmoreausterepovertyline,tofindthoseinthePeruvianpopulationatriskofacutehungeranddeprivation.Third,wecomputeinequalitymeasuresforconsumption,wealthandincome.ThecommonindicatorusedhereistheGinicoefficient,ameasurethatvariesbetween0(totallyequalsociety)to1(completelyunequalsociety).Fourth,werecordratesofchildlabor,definedaschildrenage6to14yearworkingmorethan15perhoursperweek.Startingfromthepositionthatchildlabor,especiallyatsuchyoungages,isdetrimentaltobothhealthandlearningpossibilities,wehopetofindlowanddecliningvalues.

7BothratesarederivedfromtheLSMS(ENNIV1994and1997)carriedoutbytheInstitutoCuánto.Themalnutritioncalculationsareforstunting(heightforage),definingachildasmalnourishedifitismorethantwostandarddeviationsbelowtheage-adjustedinternationalnorm.ThisisinlinewithotherstudiesofmalnutritioninPeru.Oneofthecrucialassumptionsinthesestudiesisthatage-specificnormsofheightandweightarehomogenousinthecountry,i.e.thattheydonotvarybylocationorethnicgroup.8SomeoftheseadjustmentschangetheconsumptionaggregatesuppliedbyInstitutoCuántoforbothsurveyyears.AsexplainedinAnnex2,ourmajordeviationsfromCuánto'smethodologyinclude:(a)leavingthetotalbundleofgoodsenteringintothecalculationofthepovertylineconstant(whileinPerugenerallyonlythefoodbasketisleftunchanged),(b)excludingrentfromtheconsumptionaggregateasthesurveyquestioninthissectionchangedsignificantlyfrom1994and1997,(c)interpretingthebenefittransferfromsocialprogramsdifferently,and(d)usingadifferentregionalpricedeflationmethod.

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Fifth,weareinterestedintotalschoolenrollmentsandthenumberofambulatorycarevisitstothetotalpublichealthnetwork.Obviously,theseareonlyinputs,asbythesesheernumberswecannottellthequalityofeducationorwhymorepeoplesoughtcareinpublichealthfacilities-accessand/orqualitymighthaveimprovedorpeoplemightalsobemoreinneedofcarebecausetheirhealthdeteriorated.Finally,werecordthepercentageofthepopulationwithaccesstosanitation,water,andelectricityandthepercentageofthepopulationlivinginhomeswithmudfloors.

Whilewewilllookbelowatthedispersionofsomeoftheseindicatorsbygroupsofpeopleorbyregion,thereareaspectsofsocialdevelopmentthatwedonotassesshere.Wedonotlookat,forexample,whetherdifferentgroupshavesecurepropertyrightsandthepossibilityofenforcingtheserights;i.e.,whethertheyhaveequalandfairaccesstothejusticesystem.Similarly,socialprogressofsocietywillalsobeafunctionofthedegreetowhichfamiliesandcommunitiesparticipateinlocalandregionaldecision-makingandofhowsocietyintegratesdifferencesinculturalvaluesandbeliefs.

Developments1994to1997.Lookedatfromdifferentangles,Peruhasmadeprogressinmanyareasduringthethreeyears.Table1containsthesixdifferenttypesofindicatorsoutlinedabove.Malnutritionrates(forstunting)decreasedsubstantially,inbothurbanandruralareas.Weestimatethataboutoneoutoffourchildrenbelowtheageoffiveisnowmalnourished,downfromalmostoneinthreein1994.However,thisleavesmorethan600,000childrenmalnourished,whichwilllowertheirlearningabilityandmakethemmuchmorevulnerabletoillness-nowandlaterintheirlivesaswell.TheliteracyrateofthePeruvianpopulationabovesixyearsofageincreasedandnowreaches90percent.

Povertydecreasedinthepastseveralyearsandthisisarobustresult,

quiteindependentofthepovertylinechosen.9Anespeciallypositivedevelopmentwasthereductionoftheseverepovertyrate,fromalmost19toabout15percent.Ifthesearethetruenumbers(giventhemarginoferrordescribedinthelastsection),thismeansthat600,000Peruvianshavemanagedtofindlivelihoodsthathelpedthemoutofextremeconsumptiondeprivation.However,3.5millionpeopleremaininsuchimmediatedanger.Theproportionofthepopulationinpoverty,notabletofinanceabasicbasketoffoodandnon-foodgoods,decreasedaswellbutremainsveryhigh.Halfofthepopulation,or12millionpeople,werepoorin1997.Andaswehaveseenwhenlookingatseverepovertyrates,thereductioninpovertyisnotonlylimitedtothepartofthepopulationhavingconsumptionexpendituresnearthepovertyline.Ifthiswerethecase,thepovertygapindicator(ameasureofthedepthofpovertyinrelationtothepovertyline)wouldnotshowsignificantdeclines.Ascanbeobservedinthetable,though,thegaphasbeenreducedquitesubstantially,especiallyinruralareas.

Notwithstandingthedeclineinpoverty,however,importantinequalitymeasuresshowa(modest)rise.AlthoughTable1reportsthatthedistributionofconsumption,especiallyinruralPeru,islessskewedin1997thanin1994,thedistributionofbothincomeandwealthwhichincludesavingsandhencetheaccumulationofwealth-appearstohavebecomemoreunequalinrecentyears.

9Wevariedthepovertylineoverawiderangeandfoundthatpovertyratesdecreasedquitehomogeneously.

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Table1:BasicIndicators(percent)National Urban Rural1994 1997 1994 1997 1994 1997

1.Malnutritionrate(%) 30.0 23.8 17.4 12.2 44.7 37.3Literacyrate(%) 87.6 90.2 92.3 94.3 77.4 82.1[lifeexpectancy(yrs.)] -- 68.01-- -- -- --[infantmort.(per1,000births)] -- 42.01-- -- -- --2.Povertyrate(%)3 53.5 49.0 46.1 40.4 67.0 64.7Povertygap(%) 18.9 16.0 14.4 11.8 27.1 23.5SeverePovertyrate(%) 18.8 14.8 12.9 9.3 29.5 24.53.Consumptioninequality,Gini .360 .348 .351 .345 .349 .324Incomeinequality,Gini .469 .484 .437 .441 .494 .500Wealthinequality,Gini .695 .726 .672 .705 .706 .6784.Childlabor2(%) 7.8 11.8 3.9 6.9 22.5 33.55.Schoolenrollment('000) 4,8805,0802,9603,0301,9202,050PublicambulatoryCare(4weeks,'000)

1,7602,9901,2502,160510 830

6.Electricityconnections(%) 68.8 73.7 93.7 97.4 23.2 30.3Sanitationconnection(%) 48.2 58.6 73.4 84.3 2.4 11.6Water,publicnetwork(%) 65.0 72.8 84.9 89.0 28.8 43.1Homeswithmudfloors(%) 41.0 43.3 20.4 23.2: 77.9 79.61Lifeexpectancyrateandinfantmortalityrateisfor1996.2ChildLabor:percentofallchildren,6to14yearsofage,workingmorethan15hoursperweek.3SeeAnnexTablesA2.6andA2.7foraregionalbreakdownofpovertystatisticsincludingtheestimatedstandarderrors.Source:StaffestimatesbasedonENNIV(1994,1997).Lifeexpectancyandinfantmortalityratefor1996fromWorldBank(1998).

Withrespecttochildlaborwehavetorecordanegativedevelopment.In1997,morechildrenwereworking(inbothabsolutenumbersandpercentages)thanseveralyearsearlier.Ontheotherhand,thepubliceducationandhealthsectorsservedmorestudentsanddeliveredmore

ambulatorycarein1997thanin1994,althoughtheriseofstudentenrollmentratesinpublicprimaryandpublicsecondaryschoolsisverysmall.Onecautionaryremarkisnecessaryhere:thetwohouseholdsurveysonwhichwebaseourassessmentswerecarriedoutindifferentmonthsoftheyear,the1994surveyinJune/Julyandthe1997surveyinOctober/November.Whilethisshouldnotaffectestimatesofschoolenrollmentssincebothperiodsaretermtimes,healthandillnesspatternsmightbedifferent.Itwouldthereforebedifficulttoattributetheobservedriseinambulatorycaretreatmentsinhealthcentersandhospitalstoalargerandbetterpublichealthservicealone.

Withrespecttoconnectionrates,thelargepublicinvestmentsinbasicinfrastructurethroughprogramssuchasFONCODESandFONAVIhaveincreasedtheseratessignificantly.Morethanhalfamillionhouseholdseachhaveobtainedsanitation,electricity,andpublicwater.Electricityconnectionsinurbanareasarenowalmostcomplete;urbansanitationisat85percent(whichstillleaves2.4millionurbanresidentswithoutadequatehygienefacilities)andpublicwaterreaches89percent(with1.7millionresidentswithoutwater).Inroadsinruralelectrificationandruralwaterhavebeenmadebutgapsremainverylarge.Ruralsanitation,althoughprogressingaswell,isstillscarce.Whilepublicinvestmentsininfrastructureincreasedlivingstandardsofmanyfamilies,thequalityofexistinghousingstockitselfdoesnot

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seemtohaveimproved.Actually,thepercentageofdwellingswithmudorearthfloorshaveincreasedfrom1994to1997,signalingthatasubstantialnumberoffamiliesconstructingnewdwellings-inurbanandruralareasalikedonothavetheresourcestoinstallamorehygienicandstablefloor.

Grapth2:LatinAmerica:InfantMortalityRates,1996

Source:WorldBank(1998).

Comparisons.SomecomparisonswithotherLatinAmericancountriesshowthat,despitethemajorimprovementsrecordedabove,Peruisstillcatching-upwithrespecttoseveraloftherecordedindicators.Graph2showstheinfantmortalityratein1996,settingitinrelationtoGNPpercapitaasrecordedbytheWorldBank'sAtlasmethod.AlthoughPerureducedinfantmortalityfrom54(1990)to42deathsper1,000livebirthsin1996,itisstilllaggingbehindtheregionalachievementsforcountriesofitsincomelevelanditplacesPeruamongtheworstintheLatinAmericanregion.Similarly,thematernalmortalityratefor199095of265deathsfor100,000birthsisalmostoneandhalftimeshigherthantheLACaverageandis15timestheaverageofdevelopedcountries.Forexample,bothColombiaandCostaRicahaveconsiderablylowerinfantmortalityrates(Colombia25,CostaRica12)whiletheyareroughlyinthesameincomebracketthanPeru.Thesamepicture-althoughnotaspronounced-canbe

seenforlifeexpectancy.Here,itisestimatedthatPeruhasaroughlyfouryearlowerlifeexpectancythanitsincomelevelwouldsuggest.10SuchagapdoesnotexistforadultliteracywherePeruperformsaccordingtoexpectations.

Graph3:LatinAmerica:AccesstoSafeWater,

19931997Source:WorldBank(1998).

Similarly,accesstobasicservicesinPeruisstilllowdespitethebigsuccessesachieved.Graph3showsLatinAmericancountriesandtheirpercapitaincomelevelwithrespecttothepercentageofthepopulationhavingaccesstosafewater.Whiletherelationshipisnotaspronouncedasinthecaseoftheinfantmortalityrate,wecanneverthelessalsodetectthatPeru,with72percentwaterconnectionratesfaresworsethanColombiaorMexico.CostaRica-asinmanyinstances-isthepositiveoutlier.

10SeeHicksandPeeters(1998).

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Povertyratesareverydifficulttocompareinternationally.Asoutlinedinsection2above,povertyestimatesarebasedonhouseholdsurveys,whichdifferconsiderablyinsampledesignandcontentacrosscountries.Manyrecordonlyincomesandnotconsumptionexpenditures,whichweusehereforpovertymeasurement.Povertylinesaregenerallydeterminedinnationalcontexts,withvaryinggoodsbaskets.Realprices,evenafterconvertingthemintoonecommoncurrency,alsoshowwidevariationsothatpurchasingpowerparitieshavetobeusedtoobtaincomparability.Whileeffortstomakepovertystatisticsinternationallycomparableareworthwhile,theyhavetobehandledwithextremecare.11

RegionalDevelopments

ChangesinPovertyandMalnutritionRates.WhilepovertyandmalnutritionindicatorsdecreasedinallofPeru'sverydiverseregions,ratesofchangehavebeenquitedifferent.Table2reportsthepercentageofchangebetween1994and1997;i.e.,thetablenormalizesthelevelofpovertyandmalnutritionacrossregions.Forexample,afourpercentdecreaseinabsoluteratestranslatesintoasmallerpercentagechangeinruralthanurbanPerubecausetheprevalenceofpovertyandmalnutritionismuchhigherinruralareas.ThesepercentagechangesshowthatPerumadesubstantialinroadsinreducingseverepovertyandmalnutrition.

However,thetablealsoshowsastarkurban-ruraldifferenceintheseadvances.UrbanPeruwasthedrivingforcebehindmuchofthegainsforallthreeindicators.Tworegionshaveperformedbetterthanthenationalaverage:theurbanSierraandLima.Ontheotherhand,theruralSierra-wherealmosttwo-thirdsofthetotalruralpopulationlive-hasconsistentlyperformedworsethanthenationalaverage.TheoneregionwheretheindicatorsshowanunusualtrendistheruralCoast,wherebothpovertyandseverepovertyreductionratesarebelowthe

nationalaverage,butmalnutritiondeclinesverystrongly.

Table2:PercentageChangesinRegionalPovertyandMalnutritionRates,19941997Poverty SeverePoverty Malnutrition

Lima -19 -25 -22UrbanCoast +2 -23 -16RuralCoast -4 -13 -40UrbanSierra -24 -39 -42RuralSierra -2 -16 -4UrbanJungle 0 -23 -23RuralJungle -7 -23 -26UrbanPERU -13 -28 -30RuralPERU -4 -17 -17TotalCountry -8 -22 -21Source:StaffEstimatesbasedonENNIV(1994,1997).

11InitsWorldDevelopmentIndicatorstheWorldBankusedtoincludePeruinsuchinternationalcomparisonsbut,afterreexaminingthebasicdata,ithasnowstoppedpublishingestimatedratesfortheabovereasons.

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Graph4:PercentofTotalPoorandMalnourishedin

RuralAreas,19941997Source:StaffestimatesbasedonENNIV(1994,1997)

Inaccordancewiththesepovertyandmalnutritionreductionpatterns,thedevelopmentsoverthepastfewhaveledtoahigherconcentrationofdeprivationinruralcomparedtourbanareasofPeru.Graph4showsthedistributionofthepoor,severepoorandmalnourishedchildrenbelowtheageoffivein1994and1997.Almost50percentofthepoor,60percentoftheseverepoorand70percentofthemalnourishedchildrenlivedinruralPeruin1997.Thisoccursagainstthecontinuingurbanizationofthecountryresultinginmorethantwo-thirdsofthepopulationlivinginlargeandsmallcities.

Graph5:RealperCapitaConsumptionGrowthRates,

byRegion19941997Source:StaffestimatesbasedonENNIV(1994,1997).

Table3:RegionalDispersionIndicators,LatinAmericancountries,variousyears

Year DispersionArgentina 1995 .736Brazil 1994 .424Chile 1994 .470Columbia 1989 .358Mexico 1993 .502Peru 1997 .561Source:Fallon(1998).PeruestimatefromENNIV(1997).

Dispersion12inInternationalPerspective.Inlinewiththeabove,incomepercapitaandconsumptionpercapitadifferencesacrossregionshaveincreased,andPeruhasaninternationallyhighrateofinternalregionaldispersion.PercapitaconsumptionintheurbanSierraandLimaincreasedbymorethan15percentwhilegrowthwasnegligibleintheruralSierraandevennegativeintheurbanSelva(thejungleregion)andurbanCoast(Graph5).Byinternationalstandards,theexistingregionaldispersioninPeruisveryhigh,asTable3shows.

PeruhasmuchhigherinequalitiesthanColombia,Chile,Brazil,andevenMexico,andisonlytoppedbyArgentina.

DistributionofNewSocialandInfrastructureServices.AsTable1showed,basicandsocialserviceaccessratesincreasedstronglybetween1994and1997.Morethanhalfa

12Thedispersionindicatorusedhereistheunweightedcoefficientofvariation(i.e.thestandarddeviationacrossregionsdividedbythenationalmean).SeeFallon(1998).

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millionhouseholdswerenewlyconnectedtowater,electricityandsanitation.Ambulatoryhealthvisitsincreasedbyabout60percent.Whowasreachedbytheadditionalinvestmentsmadeintheseareas?Thisisanimportantquestionforpublicpolicy,especiallygiventheincreasingregionaldispersioninPeru.

Table4:DistributionofNewAccesstoBasicandSocialServices,19941997(percentage)

Urban RuralWater 57 43 (100)Electricity 72 28 (100)Sanitation 78 22 (100)Ambulatoryhealth 74 26 (100)Education,enrollment 33 67 (100)Source:StaffestimatesbasedonENNIV(1994,1997).

QuitecontrarytobeliefabouttheruralfocusofmanyofPeru'spublicprograms,13wefindthatbyfarthelargestportionofnewbeneficiariesliveinurbanareas.AsTable4shows,exceptforthe(modest)increaseinabsoluteschoolenrollmentrates,thebeneficiarypopulationofallotherbasicandhealthserviceshasbeeninurbanareas.Indeed,thedistributionofbeneficiariesisquiteclosetotheoverallpopulationdistributioninPeru,whichwouldsuggestthatexpendituredistributionsfortheseprogramshavelargelybeendrivenbypopulationdensitiesratherthanpovertycriteria.

Table5:DistributionofNewAccesstoBasicandSocialServices199497,bypopulation

quintilewater electricity sanitation health1(poorest) 20 18 18 162 25 25 24 203 21 18 20 18

4 18 20 18 265(richest) 15 18 19 19

(100) (100) (100) (100)Source:StaffestimatesbasedonENNIV(1994,1997).

Gainsinnewaccesstobasicandsocialserviceswerequiteevenlydistributedinthepopulationanddonotshowasignificantpro-poorbias.Table5showsnewaccessbynationalpopulationquintiles,withquintile1comprisingthepoorest20percentofthePeruvianpopulationandquintile5therichest.Thepopulationquintilesareformedonthebasisofpercapitaconsumptionexpenditures.Accordingtotheresults,programsseemtobemoresuccessfulinreachingthepoorinthesecondquintilethantheseverepoorinquintile1.14Inpart,thisisdrivenbytheobservedregionaldistributionoftheadditionalexpenditures.Obviously,thesestatisticsonsupplyofserviceswilltranslateintowelfaregainsfornewbeneficiariesonlyifthequalityoftheservicesisadequate.Inanurbanqualitativeinvestigationconductedin20centrospoblados(sub-districtadministrativeunits)bytheMinistryofthePresidencyin1997,communitiesrankedthequalityofwaterandsanitationservicesastheirprimaryproblem-whiletheyhadaccess,theserviceswerenotreliable.15Similarly,especiallyinthesocialsectors,thebottleneckinmanylocalitiesmightnotbethesupplyofservicesbutratherthedemandofbeneficiaries.Thedemandforhealthcare,for

13SeeOxfordAnalytica(1998).14Oneimportantcaveathastobemadehere.Comparingquintilesbetween1994and1997inthiswaywouldassumethatthereisnomobilityamongpopulationgroups.Aslaterpointedout,thisisnotthecase.However,mobilityisoftenrestrictedtomovementtotheclosestquintile(e.g.fromthebottomtothesecondquintileorfromtherichesttothefourthquintile).Theoverallassessmentthatinfrastructureconnectionsweredistributedquiteevenlyacrossthepopulationisthereforelikelytohold.

15SeeMinistryofthePresidency(1997).

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example,willbeinfluencedbythecostsoftransport,waitingtime,medicineandalsobythecompatibilityoftheofferedserviceswithtraditionalhealthbeliefs.

InequalityanditsComponents

AfterhavingdetectedthatsocialandeconomicprogresshasnotbeenevenlydistributedinPeru,wenowwanttobrieflyreturntothefindingthat,forthefirsttimeinadecade,inequalityhasriseninPeru.Thissectionexaminesconsumption,income,andwealthchangesbyquintileandthenlooksatthesourcesofthisrisinginequality.

Graph6:GrowthinIncome,ConsumptionandWealth(averageannualgrowthinpercapitareal

terms),Peru19941997Source:StaffEstimatesbasedonENNIV1994and1997

Consumption,IncomeandWealthGrowthRates.Consumption,income,andwealthchangesrevealaquitedifferentdistributionofgainsinprosperity.Graph6showsthatpercapitaconsumptionchangeswerehighestforthepoorestandrichestquintiles.Whiletruealsoforincomechanges,gainswereclearlytiltedtowardtherichestquintile,asreflectedintheriseinincomeinequalityreportedabove.Changesinwealthofthesesamepopulationgroupsshowawidevariation,whichmightbedueinpart

tochangesinreportingbehavior.However,accordingtotheseestimatestherichestquintileagainrecordsthehighestpercapitagrowthratesofwealth16,thusincreasingwealthinequality.17Itisnotuncommontofindthatconsumptionandincomeinequalityshowdifferenttrendsmostimportantly,incomediffersfromconsumptionbyincludingsavings(ordissavings).Sincesuchsavingswilldeterminethedistributionofassetsandwealthinthelongrun,economistsgenerallytendtoassignincomeinequalitydevelopmentsmoreweightthandevelopmentsinconsumptioninequality.

Theseresultsareconfirmedbyadifferentdatasource:examiningincomeinequalitychangesbetween1995and1997,thePeruvianStatisticalInstitute(INEI)findstheGinicoefficientincreasingaswell.AccordingtopreliminaryestimatesbasedonthelargeNationalHouseholdSurvey(EncuestasNacionaldeHogares),theGinicoefficientincreasedbetween1995and199718,thussupportingthefindingspresentedhere.

16Thewealthvariableincludesthevalueofconsumerdurablegoods,thevalueofownedhouses(self-assessment),andthevalueofpropertyandequipment.Thewealthchangesreportedinthegraphcorrespondtopopulationquintilesdefinedusinghouseholdpercapitaexpenditures.17SeeAnnex2foradefinitionofincome.Inaccordancewiththedefinitionofconsumption,theincomevariabledoesnotincludetherentalvalueofthehousebecausethequestiononrentalvaluewaschangedinthe1997questionnaire.18CommunicationwithMECOVIprojectstaff,INEI.

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Table6:ExpectedChangesinIncomeInequalitybyIncomeSource,1997

(percentofGinichange)Incomesource Expected

ChangeSelf-employmentincome

-4.9

Wages 0.6Transfers 2.2propertyincome 2.1Source:Rodriguez(1998).

Sourcesoftheriseininequality.Whatarethecontributingfactorsbehindthisincreaseinwealthandincomeinequality?Wefirstlookattheimpactofthedifferentcomponentsofincome.Whatwouldhappenifoneofthecomponentsofincomeweretoincrease?Doesthislowerorincreaseinequality?Table6reportstheimpactontotalinequalityfromincreasingincomeofeachcomponentbyonepercent:incomefromself-employment(comprisingmicroenterpriseowners,professionals,andentrepreneurs)reducesinequalitystrongly(byalmost5percent),whileallothercategories-wageincome,transfersandincomefromproperty-tendtoincreaseinequality.TheriseininequalityinPeruoverthethreeyearscanbelargelyattributedtoadecliningshareofself-employmentincomeandrisingsharesoftransferandpropertyincome.

Table7:ExpectedChangesinWealthInequalitybyWealthSource,1997

(percentofGinichange)Wealthsource ExpectedChangeHousing 1.9Durablegoods -1.5Urbanproperty 1.3Agriculturalproperty -1.6

Enterprises 0Source:Rodriguez(1998).

Repeatingtheexerciseforwealth,thedrivingforcesbehindwealthinequalityarehousingandurbanproperty(Table7).Wealthisdefinedhereasthetotalvalueofhousing,durablegoods(resalevalue),urbanproperty,agriculturalproperty,andenterprises.Increasingeachofthecomponentsbyonepercent-whileleavingalltheothersconstant-wouldincreasetheGinicoefficientinthecaseofhousingandurbanpropertywhiledecreasingitifwealthfromdurableconsumergoodsoragriculturalpropertyweretoincrease.Hence,itappearsthatlanddistributionandtheallocationofdurablegoodsamonghouseholdsismoreequalthantheoverallwealthdistributioninthecountry.

Therearetwovariablesassociatedwiththeobservedrisesinincomeinequality:educationandregionalincomedifferences.First,themoreeducatedPeruviansprofitedmorefromthecurrentupswingthanthelesseducated.Thisreflectsafindingcommontomanyanalysesoverthepastfewyears,i.e.,thatincomesofthehighlyeducatedarerisingbymorethantheincomesofthelesseducated.Averageincomesoffamilieswithhighereducationroseby63percentbetween1994and1997,whileaverageincomesofthosewithprimaryeducationorlessrosebyjust5percent.Obviously,thisdoesnotmeanthatnewinvestmentineducationwouldincreaseinequalityfurtherquitethecontrary,improvingthequalityofprimaryandsecondaryeducationwoulddecreaseinequality.Second,-andasalreadyoutlinedabove,-thewideningofinter-regionaldifferenceshascontributedtoariseininequalityaswell.

Whattypesofpolicieswouldhelptoreduceincomeandwealthinequality?First,educationandtrainingofthelesseducatedandtheirchildrenwouldhelpequality.Second,abalancedregionalpatternofgrowthwoulddothesame.Here,itmightbeinterestingtothinkabouttheroleofprovincialandlocalgovernmentsinpromotingmore

equitableregionaldevelopment.Lastly,policiesthatimproveincome-earningpossibilitiesfromself-employment-suchasmicroenterpriseswouldalsotendtolowerinequality.

InternationalComparisons.Whilewehavecautionedagainstdirectcomparisonsofpovertyratesacrosscountries,astrongercasecan,however,bemadetocomparedistribution

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statisticsacrosscountriesbecausethesedonotdependonthefixingofsomerealbaseline,asisthecasewithanabsolutepovertyline.Table8showsthatLatinAmericanincomeinequalityisthehighestistheworld,evenhigherthanforSub-SaharanAfrica.WhilePeru'sinequality,measuredbytheGinicoefficient,wasabovetheLatinAmericanaverageinthe1970sand1980s,thisappearstohavechangedinthe1990s.ThereisquitegeneralagreementthatincomeinequalityinPerudecreasedfromthemid-1980stothemid-1990s.19

Table8:InequalitybyRegion(Ginicoefficients,multipliedby100)

1960s 1970s 1980s 1990sEasternEurope 25.1 24.6 25.0 28.9OECDandhighincome 35.0 34.8 33.2 33.8EastAsia/Pacific 37.4 39.9 38.7 38.1SouthAsia 36.2 34.0 35.0 31.9MiddleEast/NorthAfrica 41.4 41.9 40.5 38.0Sub-SaharanAfrica 49.9 48.2 43.5 47.0LatinAmerica 53.2 49.1 49.8 49.3Peru n/a 55.0 51.8 47.2Sources:IMF(1998,p.2).Peru'sratesfor1980s(=1985)fromSaavedraandDiaz(1997),for1990s(=average1994and1997)fromRodriguez(1998).

However,intheperiodfrom1994to1997,incomeinequalitywasontheriseforthefirsttimesince198586,veryclosetotheLatinAmericanaveragewithaGinicoefficientof48.5.Graph7showsthelatestestimatesofincomeinequalityinLatinAmericancountries.PeruhasconsiderablymoreequalitythanBrazil,Colombia,andalsoMexicobutlessthanCostaRica,Venezuela,andBolivia.

Graph7:LatinAmerica:IncomeInequality

(latestavailableyear)Source:WorldBank(1998).

19SeeSaavedraandDiaz(1997)andEscobaletal(1998).Contrarytotheabovedatashown,LondoñoandSzékely(1997)findthat,overall,incomeinequalityinLatinAmericaincreasedsignificantlyduringthe1980sbutthatinequalityhassubsequentlynotdecreased.

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4.Poverty-ChangingFaces?Thissectionlooksathowdifferentgroupsinsocietyhavefaredoverthepastyearsandhow-ifatall-themainfactorslinkedtopovertyhavechanged.Wheneverpossible,wewillalsomakereferencetosomeoftheotherwelfareindictorslookedatintheprevioussection;however,datalimitationswillrestrictustoconcentratinglargelyonconsumptionpoverty.

Wewillabstainfrompresentingafullpovertyprofileinthissection-muchhasbeenwrittenandisbynowwellunderstoodaboutthemaincausesandcorrelatesofpovertyinPeru.20Tobrieflysummarize,nevertheless:comparedtobetter-offgroups,thepoorcontinuetoliveinworseandsmallerdwellings,generallywithadobewallsandearthfloors.Theyhavelessaccesstomarkets,especiallyinruralareas,andtheirpossessionsarelimited;almostalloftheurbanpoorhaveaccesstoradios,mosttoTVs,butonlyoneinfivefamilieshasatelephone.Withfewexceptions,therearenotelephonesatallinruralPeru.Electricityconnectionsinthecitiesarealmostuniversalbutonlyaboutafifthoftheruralpoorcanrelyonelectricityforlighting.Poorcitydwellersstillhavetocookwithkerosene;theruralpoor-iftheycan-relyonwood.About40percentofthepoorcan'taffordtoseeadoctorornursewhentheyaresick.Withhealthaccess,especiallyinruralareas,stillsparse,transportation,waitingandmedicinecostsaresimplytoohighandonlytenpercentofthepoorarecoveredbysomeformofhealthinsurance.Finally,educationstillisoneofthemaindrivingforcesbehindwelfaredifferencesinPeru-lookingattheaverageyearsofeducation,poorhouseholdheadsinurbanareashaveabout6.5yearsofformaltrainingandnon-poorheads9years.EducationalattainmentinruralPeruisevenlowerandsoisthegap

betweengroups:forpoorhouseholdheads4.5years(lessthanneededtofinishprimaryschool)andfornon-poorones6years(orbarelyattendanceofsecondaryschool).

Insteadofdescribingstaticdifferencesinlivingconditions,weareinterestedherehowpovertyriskshavechangedovertime.Thatis,bybelongingtoaspecificgroupinsociety,e.g.anagegrouporethnicgroup,howhighwastheriskofbeingpoorin1994?Andhowdidthisriskchangeovertime;diditincreaseordecrease?Suchananalysiswillhelpustoidentifyrelativetrends,e.g.,hastheindigenouspopulationcaughtuptothedevelopmentsforthenon-indigenousgroups?Orhasthegapbetweenthemincreasedandtheirdegreeofeconomicexclusionwidened?

Theselectionoftheserisksandtheirrelativeimportancefollowsananalysisofhundredsofidenticalhouseholdsin1994and1997(seeBox1andAnnex1).Thisallowsustosingleoutthemostimportantfactorsdeterminingwelfarechanges.

20See,forexample,MoncadaandWebb(1996).

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Box1:WhatInfluencesSuccessorFailure?ResultsfromStudyingIdenticalHouseholdsOverTime

Examininghow900identicalhouseholdsfaredbetween1994and1997shedslightonthedeterminantsofhouseholdwelfaredynamics.AsAnnex1describesinmoredetail,westudiedthedeterminingfactorsofpercapitaconsumptiongrowth.Resultsindicatethat:

a.Female-headedhouseholdshadhigherpercapitagrowthratesthanmale-headedhouseholds;

b.Migrantfamiliesdidnorfareworsethannon-migrantfamilies;

c.Nativelanguagespeakersclearlyfellbehind.Oneofthestrongestresultsisrelatedtolanguage,andwithitethnicity.Evenwhenwecontrolforothervariablesthatarecorrelatedwithlanguage,suchasgeographiclocation,nativelanguage-speakinghouseholdsstillfallfurtherbehindSpanish-speakinghouseholds;

d.Infrastructureisofmajorimportanceandwefindincreasingreturnstoservices.Wefindevidenceofincreasingreturnstothenumberofservicesthathouseholdscommand.Hence,ahouseholdwithfourservices(telephone,water,electricity,andsanitation)obtainsmorethandoublethewelfareimprovementthanhouseholdswithtwoservices.Lookingatservicesbytype,electricityisthemostimportantservicelinkedtohouseholdwelfareimprovementsinruralareas,whileatelephoneappearstobethemostimportantserviceinurbanareas;

e.Accesstosavingsincreasepercapitagrowthrates;

f.Householdsizeimpactswelfare.Wefindthathouseholdsizesignificantlyinfluenceswelfaredynamics.Largerhouseholdsfareworsethansmallerones,aslargerhouseholdsalsotendtohavehigherdependencyratios(rationofincometonon-incomeearningmembersofhousehold).Withhigherdependencyratioshouseholds

membersofhousehold).Withhigherdependencyratioshouseholdsmaytosavelessleadingtolowerwelfarechangesovertime.

g.Bettereducationandmoreexperiencemeansfasteradvance.Thehighertheeducationofthehouseholdheadin1994,thelargerthegrowthinpercapitaexpenditures;

h.Householdswithhome-basedbusinessoroff-farmemploymentopportunitiesfarebetter.bothurbanandruralhouseholdsthatuseatleastoneroominthehouseforbusinesspurposesachievedsignificantlyhighergrowthofwelfarethanhouseholdsthatdonot.Closelylinkedtothis,wefindsomeevidencethathouseholdswiththeheadofthehouseholdemployedintheinformalsectordefinitelydidnotdoworse(butratherbetter)thanhouseholdswiththeheademployedintheformalsector.

PovertyComparisons-HowDidGroupsinSocietyFare?

Thissectiontakesacloserlookatanumberofdifferentgroupsinsocietythathave,inthepast,beenidentifiedasparticularlypoor.Theseincludethenative-speakingpopulationandweuselanguagehereasacorollaryofethnicity,childrenofdifferentages,adolescents,women-headedhouseholds,ruralwidow-headedhouseholds,migrantsandthelandless.Ourmainaimsaretoseewhethermembersofthesegroupsareparticularlyatriskofbeingpoorandwhethergroupcharacteristicsareimportantinthechangesinthisrisk.Whilewewillbrieflytouchonotherdimensionsofwell-being,suchaspoliticalandsocialintegration,wewilllimitourselvesmainlytothismaterialviewofpoverty.

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Table9:RelativePovertyRisksofSelectedGroups--MoreorLessLikelytobePoor?(percent)

National PercentTotal

1994 1997 Poor,1997Nativelanguagespeakers +40.2+48.7[20.9]Children,05years +26.2+27.4[18.4]Children,614years +24.6+25.3[15.5]Youth,1517years +5.3 +8.6 [6.7]Ruralhouseholds,landless +3.5 -3.7 [16.2]Ruralwidow-headedhouseholds

-5.1 -14.2 [2.5]

Femaleheadedhouseholds -12.8 -16.5 [10.7]Migrants -16.3 -17.8 [28.2]Source:StaffestimatesbasedonENNIV(1994,1997).Theentriesinthetablearesimplerelativepovertyrisksanddonottakeintoaccounttheinfluenceofothervariables.Regressionresultsfromthepaneldataanalysis,whichguidedusintheselectionofvariables,areincludedinBox1(seealsoAnnexI).Povertyrates,asinthewholereport,arebasedonconsumptionpercapita.

Table9reportspovertyrisksforeachgrouprelativetotheothermembersofsociety.Apositiveentrymeansthatthepopulationbelongingtothisgroupismorelikelytobepoorthantherestofthepopulation;anegativeentrystandsforthereverse.Hence,thesearenotabsolutepovertyratesbutrelativeonescomparedtoallothergroups.ThelastcolumnofthetableshowstheshareofthetotalpoorpopulationinPerubelongingtothisgroup.Thelatterisimportantforpolicymakersasthepovertyriskmightbeextremelyhighforagroupinthepopulationbuttheymightrepresentonlyatinyfractionofthetotalpoorpopulation.

Native-speakingPopulation.Thenative-speakingpopulation21is,ofallthegroupsconsideredhere,theonewiththehighestrelativepovertyrisk,andwefindthisriskincreasing-whichimpliesthatthenative-speakingpopulationisfallingfurtherbehindtheSpanish-speakingpopulation.Weuselanguageasaproxyforindigineitybecauseindigeneitycannotbedefined-indigenouslanguages,traditionalclothing,heritage,andobservedtraditionsandbeliefscan,butneednot,bepartofthelifeofindigenouspeople.Accordingly,estimatesoftheindigenouspopulationvarybetween10and40percentofthepopulation.However,withlanguagebeinganintegralpartofindigenousculture,weemployithereasaproxyforindigeneity.Wefindthatthenative-speakingpopulationwas40percentmorelikelytobepoorthantheSpanish-speakingpopulationin1994and49percentmorelikelytobepoorin1997-inotherwords,nativespeakersarefallingbehind.Nativelanguagewasalsooneofthemostrobustandimportantfactorswhenweexaminedwelfarechangesofseveralhundredidenticalhouseholdsbetween1994and1997(seeBox1)-controllingforeverythingelse(e.g.education,geographiclocation,experience,householdsize),thenative-languagespeakingfamilieshadsignificantlylowerconsumptiongrowthratesthantheSpanish-speakingpopulation.

IntegrationoftheindigenouspopulationhaslongbeenrecognizedasoneofthemostimportantchallengesinthefightagainstpovertyanddeprivationinPeru.Educationlevelsof

21Weclassifyallthosehouseholdsasnative-speakingforwhichthehouseholdheadreportedthatherorhismothertongueisQuechua,Aymara,Campaoranothernativelanguage.SeeMacIsaacandPatrinos(1995)orDavisandPatrinos(1996).

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adultsarelowandilliteracylevelsarestillsubstantial(21percentoftheruralnativespeakingpopulationabove6yearsoldareilliterate).Schoolattendanceofindigenouschildrenissignificantlybelowthenationalaverage,andchildrenfromindigenousfamiliesaremorethantwiceaslikelytobemalnourishedthanchildrenfromanon-indigenousbackground.Otherfactorssuchaseducationorexperiencebeingequal,nativelanguagespeakersearnlessincome.22Dueinparttothefactthatthemajorityofthenative-languagespeakingpopulationlivesinruralareas,itsaccesstoelectricity,sanitation,water,andhealthservicesislowerthanfortheSpanish-speakingpopulation.

Table10:DistributionofNewAccesstoRuralBasicandSocialServices,byLanguage,19941997(percentage)

NewaccessNativeSpeakers

Non-NativeSpeakers

Waterconnection 22 78 (100)Electricityconnection

47 53 (100)

Sanitationservices 60 40 (100)Ambulatorycare,hospital

23 77 (100)

Ambulatorycare,prim.clinic

48 52 (100)

memo:Dist.ofseverepoor

60 40 (100)

Dist.ofruralpoor 48 52 (100)RuralPopulation 42 58 (100)Source:StaffestimatesbasedonENNIV(1994,1997).

Examiningthedistributionofnewaccesstobasicandsocialservices

from1994to1997inruralareas,successinreachingthenative-speakingpopulationwasmixed.Onlynewsanitationinvestmentswentmostlytonativespeakers.Allothers,andespeciallywaterandambulatoryhospitalcare,reachedmainlythenon-indigenouspopulation.Thesefiguresareparticularlysignificantinlightofthecompositionoftheextremepoorwerenativespeakersin1997:almost60percentoftheextremepoorwerenativespeakers.

TheabovesuggeststhattheGovernmentofPeruneedstotakeacarefullookatitsattemptstoreachoneofthemostdeprivedgroupsinthecountry,itsindigenouspopulation.With60percentoftheseverepoorinruralareasbeingnativespeakersandthemassivepublicinvestmentsoverthethreeyearsunderstudyhavinghadonlylimitedsuccessinreachingthem,onepossibilitywouldbetotrytobringingroupsthathavelongworkedinandwithisolated,poorcommunitiesaspartnersinthepovertyreductioneffort.TheMinistryofthePresidencyinitsLuchacontralaPobreza(fightagainstpoverty)hasattemptedsuchapartnershipapproach,especiallyinruralareas,andnowworkscloselywithanumberofrespectedandknowledgeableNGOstofacilitate,plan,andimplementcommunity-basedprojects.Whileanevaluationofthisapproachremainstobecarriedout,itdoesrepresentaninnovativeandverypromisingwaytochannelingmuch-neededhelptotheseverepoorindigenouspopulation.

Children.Intheagedistribution,childrenarethepoorestgroupinPeruviansociety.Moreprecisely,manychildrenliveinpoorhouseholds,sincewedefinepovertyatthehouseholdlevel.23Childrenbelow14yearsoldhada25percenthigherriskofbeingpoor

22MacIsaacandPatrinos(1995).SeealsoLopezanddellaMaggiora(1998,p.2021),whofindthat,controllingforotherfactors,nativebackgroundreducesincomeoffarmersandnon-farmworkersby44percent.Theyreport,though,thatthisdifferencedisappearsaftercontrollingforvillageeffects,whichcouldbeaproxyforgeographic

isolation.23Householdsurveyscontainverylimitedinformationabouttheintra-householddistributionofresources.Hence,ifahouseholdispoorthenallofitsmembersareassumedtobepooralthoughthisneednotbetrue.Similarly,dependingontheintra-householdresourcesdistribution,'non-poor'householdsmighthave

(Footnotecontinuedonnextpage)

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Table11:ChildLabor,1994and1997(percentofchildrenages6to14)morethan15hoursperweek

morethan10hoursperweek

quintile 1994 1997 1994 19971 11.9 16.7 17.5 24.32 7.7 13.1 11.9 21.13 7.4 10.1 9.2 16.34 6.4 9.2 8.7 14.35 2.0 6.1 4.3 8.5Total 7.8 11.8 11.3 18.1no.('000)

375 616 549 940

Source:StaffestimatesbasedonENNIV(1994,1997).

thantherestofthepopulationandthisrelativeriskslightlyincreasedoverthethreeyears.Wealsofindaratherworryingtrendwhenlookingatchildlaborrates(Table11):thesedoubledforchildrenbetween6and14.Childlaborismuchhigherinthepoorersegmentsofsociety.Almostoneoutoffourseverelypoorchildrenworkedmorethan10hoursperweekin1997.Bothofthesetrendspointtochildrenremainingaparticularlyvulnerablegroupinsociety.24

Onthepositiveside,malnutritionrateshavedeclinedstrongly,bybothregionandgender.Table12showsthatmalnutritionintheruralSierraremainsveryhigh;almosteverysecondchildismalnourished.AqualitativeandquantitativeinquirybyCaritas(1997)inselectedSierracommunitiesconfirmedthehighprevalenceofmalnutrition.Girlsremainslightlymoreatriskofbeingmalnourishedthanboys,butthegendergapappearstobeclosingslowly.PreliminaryresultsfromexaminingthedeterminantsofmalnutritionratesconfirmearlieranalysesinPeru:themaindeterminantsarethepovertylevel

(householdconsumption)andeducationalstatusofthemother.Accesstobasicservicessuchascleanwater,sanitation,andelectricitycorrespondswithdecreasingmalnutritionlevels.

Table12:MalnutritionRatesbyRegionandGender,1994and

1997(percentofchildrenbelowage5)quintile 1994 1997Lima 12.1 9.0Urb.Coast 12.1 10.0Rur.Coast 32.4 20.1Urb.Sierra 27.9 14.7Rur.Sierra 47.9 45.7Urb.Jungle 28.7 23.4Rur.Jungle 44.7 36.4Totalgirls 31.6 24.8Totalboys 28.8 22.9Totalcountry 30.1 23.8Source:StaffEstimatesbasedonENNIV1994and1997.

Youth.Thethirdagegroupwefindatincreasingrelativeriskofpovertyisadolescents.Whiletheywereabout5percentmorelikelytobepoorthanallotheragegroupsin1994,theywere8.6percentmorelikelytobepoorin1997(seeTable9).Adolescentsareofparticularconcern,especiallyinurbanareas,fortwoadditionalreasons:first,itistheonlyagegroupforwhichunemploymentratesremainveryhigh-forallotheragegroups,open

Table13:UnemploymentRatesbygender,MetropolitanLima,19921996

1993 1994 1995 1996male1418yrs 19.4 12.1 14.9 18.2Totalmale 10.0 9.0 7.1 7.2

female1418yrs 21.0 11.8 11.4 13.9Totalfemale 12.4 12.0 8.7 8.5Source:EncuestadeHogares,MinistryofLabor,andSaavedra(1998).

(Footnotecontinuedfrompreviouspage)

poormembersaswell.Thediscussionaboutchildpovertyshouldthereforebemorepreciselyframedas''childrenlivinginpoorfamilies".24SeealsoRodriguezandAbler(1998).TheyfindtheresultthatchildlaborinPerutendstobepro-cyclical,i.e.,fallingwithaneconomicdownturnandincreasingwithaneconomicboom.

Page23

unemploymentdroppedaftertherecoverystartedatthebeginningofthe1990s.AsshowninTable13,unemploymentratesincreasedsubstantiallyforbothfemaleandmaleadolescentsbetween1995and1996inLima.Second,theyoungarealsoincreasinglyinvolvedinviolentacts.ArecentsurveybytheStatisticalInstituteINEIshowsthatyoungpeopleareheldresponsiblefor90percentofactsofvandalismandabout25percentofactsofphysicalviolence.

Landless.Anthropologicalstudiesgenerallyindicatethattherurallandlesspopulationisaparticularlypoorgroup.Accordingtothehouseholdsurveys,however,whilethelandlessruralhouseholdswereslightlymorelikelytobepoorthantheruralhouseholdsowninglandin1994,thisrelativeriskhasdisappearedinthepastseveralyears(Table9).Sociologicalstudiespointout,though,thattheimpactoflandlessnessmightnotshowupinofficialdata,sincehouseholdsledbytheelderlyorwidowsoftendonothavethephysicalstrengthtoworktheirownlandafterthepreviousheadofthehouseholdhasmigratedordied.Thesewouldbedefactolandlesshouseholds(althoughnotidentifiedassuch)astheydonotderiveincomefromfarmingtheirland.25Wetestedthisassertionbycomputingtherelativeriskofruralwidow-headedhouseholdsbeingpoor(Table9).Itappearsthatthesehouseholds,astonishingly,farebetterinrelativetermstootherruralhouseholdsandthattheirrelativeriskofpovertydecreasedovertheyears.

Graph8:SecondarySchoolEnrollment,byAge,1997

Source:StaffEstimatesbasedonENNIV(1997)

Gender.Viewedfrommanydifferentangles,gendergapsinPeruseemtobeclosing.First,householdswithfemaleheadshavefaredbetterthanmaleheadedhouseholdsoverthelastyears.Theirrelativeriskofpovertyisconsiderablylowerandcontinuestodecline.Similarly,whenexaminingwhichgroupofhouseholdsdidwelloverthethreeyears,wefoundthatfemaleheadship-controllingforallotherfactors-hadastrongpositiveinfluenceonpercapitaexpenditures(Box1).Second,labormarketdiscrimination(i.e.womenearninglessthanmenalthoughtheyhavethesameeducation,experience,andage)hasdisappearedintheurbanformalandinformalsectors.26However,womencontinuebedisadvantagedisruralnon-farmemployment.27Third,malnutritionratesarenotequalyetbetweenboysandgirlsbutthegapisslowlynarrowingaswell.Finally,regardingeducation,ofmostconcerninthepastwassecondaryschoolenrollmentofgirls.Graph8,whichshowsthepercentageofsecondaryschoolattendanceby

25See,forexample,Luerssen(1993).26SaavedraandChong(1999).27LopezanddellaMaggiora(1998).

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agegroupofthepopulation,alsoconfirmsthat,atleastintermsofschoolattendance,thereisnowalmostnodifferencebetweenboysandgirls.Participationratesinthelaborforcedoremainconsiderablylowerforwomenthanformen.Increases,however,arefasterforwomen.

Table14:WomenatHighLevelsofPowerandDecisionmakingseatsheld

inparliament

(%women)

administrators&managers(%women)

prof.&tech.

workers(%

women)Bolivia 6.4 16.8 41.9Brazil 6.7 17.3 57.2Colombia 9.8 27.2 41.8CostaRica

15.8 21.1 44.9

Mexico 13.9 20.0 43.6Peru 10.8 20.0 41.1Uruguay 6.9 25.3 62.6Venezuela 6.3 17.6 55.2Source:UnitedNations(1997a).

Brieflylookingattheroleofwomenathighlevelsofpoweranddecisionmaking,womenaccountforabout11percentofseatsinparliament,20percentofadministrators,and40percentofprofessionalandtechnicalworkers.Althoughstillfarbehindmen,women'sroleinpoliticsandmanagementinPeruisaboutcomparabletothatofitsneighbors(Table14).PerudoeslagbehindotherLatinAmericancountriesregardingtheroleofwomenasprofessionaltechnicalworkers,though.Also-asexploredbelowinmoredetail-anewproblemofurbanpoverty,socialviolence,especiallyaffectswomen.

Migrants.Basedontherelativeriskofbeingpoor,migrantfamiliesappeartobeintegratingwellintotheirnewenvironment.Suchfamilieswereat16percentlowerriskofbeingpoorin1994thannon-migrantfamiliesandat18percentlowerriskin1997(Table9).Whilemostrural-to-urbanmigrantsstatethattheymigrateforincomeandemploymentreasons,theireducationalleveltendstobehigherthanthatofnon-migrantfamilies,whichexplainstheirrelativelygoodeconomicintegrationincitiestowhichtheymigrated.28Also,migrationisoneofthestrongestfactorslinkingtheruralandoftenindigenouscountrysidewiththegenerallymestizocitiesbecausemigrantsmaintaintheirrurallinksandcommunitynetworks.29

InternallyDisplaced.Onegroupoftenconsideredataveryhighriskofdeprivationistheinternallydisplacedpeoplewhohadtoleavetheirruralresidenceforreasonsofpoliticalviolence.TheUnitedNationsestimatesthatstilltoday,yearsafterthemarkeddeclineofpoliticalviolence,abouthalfamillionPeruviansareinternallydisplaced.30Theseareespeciallyrural-ruralmigrantswhohavehadtoleavetheirhouse,land,andfamilynetworksandhavenot(yet)returnedtotheiroriginalplaceofresidence.Tohelpfamiliesresettletotheirhomes,thePeruvianGovernmentcreatedtheProyectodeApoyoalReboplaminetoyDesarrollodeZonasdeEmergencia(PAR)in1993.Bytheyear2000,theprogramplanstohavehelpedatotalofonemillioninternallydisplacedpersons.

28SeeEscobaletal(1998)andWhiteetal(1995).29Altamirano(1988).30UnitedNations(1997b).

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PovertyComparisons-SomeKeyFactorsinWelfareChanges

Table15:PovertyRisksofSelectedFactors--MoreorLessLikelytobePoor?(populationpercentages)

National PercentofTotal

1994 1997 Poor,1997Householdsusinghouseforbusinesspurposes

-28.2 -29.0 [10.9]

Ruralhouseholdswithatleastonememberinoff-farmempl.

-24.0 -22.7 [18.2]

Householdswithspouseorpartnerofheadworking

-10.8 -20.6 [35.6]

Householdswithoutwaterandsanitation

+54.2 +49.5[35.7]

Householdswithoutelectricity +63.0 +68.5[37.6]Householdswithheadlessthansecondaryeducation

+72.8+72.3 [61.7]

Householdsof7personsormore

+71.4+106.4 [31.7]

1spouseworkingisdefinedinremuneratedworkinthelastsevendaysbeforethesurveywasconducted.Source:StaffestimatesbasedonENNIV(1994,1997).Theentriesinthetablearesimplerelativepovertyrisksanddonottakeintoaccounttheinfluenceofothervariables.Regressionresultsfromthepaneldataanalysis,whichguidedusintheselectionofvariables,areincludedinBox1.Povertyrates,asinthewholereport,arebasedonconsumptionpercapita.

Wenowturnfromafocusongroupstoarecapoffactorsthatunderliepovertychanges.Obviously,thesetwocategoriesareoftenintrinsicallyinterlinked.Thenative-speakingpopulation,forexample,isatahigherrelativeriskofpovertythantheSpanish-speaking

population,partlybecausetheireducationattainmentsarelower,theiraccesstomarketsisscarcer,andtheirdependencyratiosarehigher.Thefactorsanalyzedbelow,however,aresignificantindependentlyof-orbetter,inadditionto-lookingatdifferentgroupsinsociety.Again,theirselectionisbasedmainlyontheexaminationofhundredsofidenticalhouseholdsovertimeandrelatingthechangeintheirwelfarelevel(consumptionpercapitagrowth)tohouseholdandindividualmembercharacteristics.Table15reportstherelativerisksofpovertyforsuchfactors.Asabove,theinterpretationofthedataisrelativetotherestofthepopulation.

HousesUsedforBusinessPurposes.Inboth1994and1997,Peruvianslivinginhouseholdsthatwereabletouseatleastpartoftheirhouseforsomeincome-generatingactivitywerealmost30percentlesslikelytobepoorthanthepopulationnothavingsuchanincomepossibility.Andthiswasoneoftheveryrobustandstrongfactorswhichwefoundhelpedfamiliesadvanceoverthelastyears(Annex1).Suchbusinessescanbeformal(e.g.,aformalstoreinthehouse,professionalsworkingfromhome),butinthelargemajorityofcasesareinformal.Rentingoutaroom,performinghome-basedpiecework,sellingmerchandiseoutofthehouse,orsmallmanufacturingonasub-contractbasiswouldfallunderthiscategory.

Tothedegreethatlegalhomeownershipisrelatedtothehomebeingusedforbusinesspurposes,thecurrentdrivetoprovidetitlesforurbandwellingsinPerucanindeedbeofmajorimportanceforthepoor.HomeownershipinPeruisverylarge,withaboutthreeoutoffourfamilieslivingintheirownhouses.This,interestingly,doesnotvarymuchwiththepovertyleveloffamilies.However,manyofthepoor,especiallyinLima,whoinvadedtheirlandinthebigmigrationflowattheendofthe1980sandbeginningofthe1990s,donothavelegaltitletotheirproperty.If,asfoundinseveralqualitativeandquantitativestudies,31legal

31See,forexample,Moser(1996)andPersaud(1992).

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homeownershipencourageshomeinvestmentandthisraisesthelikelihoodofusingthehomeasanincome-generatingasset,thecurrenturbanpropertydrivecanhaveverypositivepovertyeffects.

Thefindingthatsuchinformalbusinessescanbeimportantforhelpingfamiliesadvanceisinlinewitharatherpositive,oratleastneutral,viewoftheinformalsectorinPeru.Informalityremainshuge,accountingforalmosthalfofurbanemployment.However,fortheself-employedwhoopenmicroenterprises,informalsectoremploymentinPeruislargelyachoice.Peoplearenotforcedintoinformalitybydistortionarypoliciesorlabormarketpractices.Thosepoliciesweredismantledtoaverylargeextentatthebeginningofthe1990s.Themainreasonforremainingintheinformalsectorinself-employmentisentrepreneurialskill.32ConfirmingthisviewoftheinformalsectorinPeru,householdswhoseheadwasemployedintheinformalsectorhadahigherpercapitagrowthrateofconsumptionthanhouseholdheadsworkingintheformalsectorevenwhenwecontrolforotherfactors.Forinformalwageearnersthepictureisdifferent.Here,segmentationstillexists-i.e.,giventheireducation,experienceandotherindividualcharacteristics,wageearnersintheinformalsectorareearninglessthantheywouldintheformalsector.Suchworkerstendtobeyoung,andsingle,notheadsofhouseholds.Hence,itissuggestedthattheylackexperienceandareinawaitingpositiontofindformalsectoremployment.

Services.Householdswithoutbasicservicessuchaswater,electricity,sanitation,andtelephonesareatamuchhigherrelativeriskofbeingpoorthanhouseholdsthatcommandtheseservices.Obviously,wewillfindamutualdependencebetweenpovertylevelandservicesaccess:poorerhouseholdstendtobelocatedinpoorerneighborhoodssothatthelikelihoodofthemhavingaccessislow.Simplystatingthataccessislowerdoesnotimplythatthereisacausallinkwithpoverty.However,inthepanelanalysisofidenticalhouseholds,wefoundvery

strongevidencethathouseholdsthathadaccesstobasicservicesin1994hadasignificantlyhighergrowthrateofpercapitaconsumptionthanhouseholdsthatdidnothavesuchaccess.Manyreasonsforthiscanbefound,suchasapositiveimpactonhealththroughcleanwatersupplyandsanitationservicesortheimportanceforhomeenterprisesofelectricityandphoneconnections.

Graph9:BundlingServices:IncreasingReturns

(increaseinconsumptionpercapitagrowthrate,19941997)Source:StaffestimatesbasedonENNIV(1994,1997).

Furthermore,thebundlingofservicesisveryimportantforhouseholds.Theadditionalpositiveimpactofeachnewserviceincreaseswiththetotalnumberofservicesavailable.Basedontheanalysisofthehouseholdpanel,weshowinGraph9thataddingafourthservicehasaboutseventimesahigheradditionalimpactthanlinkingasecondservicetohouseholds.Hence,thejointprovisionofservicesisimportanttorealizewelfareeffects:forexample,

32SeeSaavedraandChong(1999)andYamada(1996).

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cleanwateraccesswillimprovehousehold'swell-beingmoreifitcomestogetherwithsanitation.Healthrisksmightdeclinewithwateraccessbuttherealbenefitmightonlymaterializeiftheservicesareprovidedtogether.

Thepositiveimpactofsuchbundled,integratedinterventionsinPeruhasbeenobservedinadifferentstudy.Inarecentstudy,electrificationandsanitationserviceswerefoundtoincreasethereturnstoeducationsignificantlyinruralandurbanPerualike-aschildrencanreadandstudylongeratnight,theyprofitmorefromschooling.Sanitationislikelytolowerillnessandmalnutritionandhaveapositiveeffectonlearning.Also,betterruralroadsandruraltransportwereshowntohaveaverypositiveimpactonthereturnstoruraleducation.33

Table16:UrbanPeru:EducationalPremia,1991and1996(percent)

19911996changePrimary/noeducation 40.033.0 -7.0Secondary/primary 7.017.0 10.0Non-universityhigher/secondary

13.025.0 12.0

University/non-universityhigher

47.070.0 33.0

Source:Saavedra(1998).

Education.Educationalattainmentremainsnotonlyoneofthecentraldeterminingfactorsofpovertylevels,butitalsodetermineswhoadvancesrapidlyorfallsbehindinthePeruviansociety.InTable15,weseethatin1994Peruvianslivinginanhouseholdwhoseheadhadlessthansecondaryeducationwere70percentmorelikelytobepoorthantherestofthepopulation.Thishugerelativeriskstayedconstantuntil1997,butthepanelstudyshowedthatthehighertheinitial

educationofthehouseholdhead,thehigherwaspercapitaconsumptiongrowth:thebettereducatedhavebenefitedproportionatelymorethanthelesseducatedinrecentyears.ThisisinlinewithmanyfindingsinPeruthatnotonlyhavereturnstoeducationincreasedacrosstheboardsincethebeginningofthe1990sbutthattheyhaveincreasedmoreforthosewithbettereducation.Table16showseducationpremia(i.e.,thedifferenceinincomelevelsaccordingtoeducationalattainment)forurbanPeruin1991and1996.Educationalpremiaincreasedmoststronglyforuniversity-educatedPeruvians,andhencewasoneofthedrivingforcesbehindtheincreaseininequalityoverthepastyears.Asasidenote,Peru'sreturnstoeducationarenotbelowthoseobservedinotherLatinAmericacountries.AndtogetherwithColombia,Chile,Argentina,andCostaRica,educationreturnshaveincreasedduringtheperiodofstructuralreforms.

Graph10:SecondarySchoolEnrollment,RuralPeru,1997Source:StaffEstimatesbasedonENNIV(1997).

Enrollmentinsecondaryschool,itsquality,andfinancingremainsamatterofconcernintheeducationsector.Bothprimaryandsecondaryschoolenrollmentrateshaveincreasedsteadilysincethebeginningofthedecade,andgapsinenrollmentratesbypovertylevelhavedisappearedforschoolbeginners.Differencesinschoolattendanceremainforsecondary

33SeeEscobaletal(1998).

school,especiallyinruralareas,asGraph10shows:forthepoorestgroup(bottomquintileofthepopulation),enrollmentratesarestillconsiderablylowerthanforchildrenfromwell-offfamilies.Qualityindicatorsshowthatmuchremainstobeimprovedinthesector:alargedifferencebetweennetandgrossenrollmentratesindicatesthatmanychildrenareinprimaryandsecondaryschoollongerthantheyshouldbe.Anddropoutratesinsecondaryschoolhaveincreasedbetween1994and1997.Table17showsthisincreaseandalsothecontinuing,verystronglinkbetweendropoutratesandpovertylevels.34

Table17:DropOutRatesinSecondarySchool,1994and1997(percent)

quintile Urban Rural1994 19971994 1997

1 11.0 22.0 14.0 27.02 8.0 18.0 15.0 22.03 6.0 8.0 13.0 9.04 4.0 8.0 15.0 11.05 3.0 4.0 15.0 4.0Source:StaffestimatesbasedonENNIV(1994,1997).

Althoughhavingincreasedby30percentinrealtermsfrom1994to1997,educationexpendituresarestilllowinhistoricalperspectiveandhighlytiltedtowardthemorewell-offregionsofthecountry.Itisestimatedthateducationalpercapitaexpendituresin1997wereroughly20percentbelowtheir1970level.35Andthesepercapitaexpendituresaresignificantlyhigherinbetter-offdepartments.Graph11plotspercapitastudentexpendituresbydepartmentagainsttheFONCODESpovertyindex;thepoorerthedepartment,thelowertheperstudenteducationalexpenditures.SuchaspendingpatternperpetuatesregionalandgeneralinequalityinPeru.

Graph11:PovertyIndexandCurrentPerStudentPublicExpendituresInBasicEducation,byDepartment-1994

Source:Saavedra,MelziandMiranda(1997).ExpenditurescomsfromGRADE'seducationaldatabase,thepovertyindexfromFONCODES.

HouseholdSizeandDependencyRatio.Wefindthathouseholdsizeisnegativelylinkedtowelfaredevelopmentsovertime.Inpart,thelinkbetweenhouseholdsizeandwelfaredevelopmentswillworkthroughthetendencythatlargerhouseholdsalsohavemore

34Wecalculatethedropoutratesbylookingataconstantagecohort,the16to19yearoldsinbothyears(1994and1997).SinceGraph10showsthatalargepercentageofthatagecohortstillattendssecondaryschool,thecalculatedratesarelikelytounderestimatethetruedropoutrates.35Saavedra(1998).

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dependentsperincomeearner.Suchahigherdependencyratiowilllikelymeanthathouseholdscannotsavemuchoftheircurrentincomeforthefutureandconsumemostofitatpresent.Theirfutureearningandconsumptionpossibilitiesarehencereduced.

Off-farmEmployment.Off-farmemployment,althoughstillverythin,hasthepotentialtobearoadoutofpovertyinruralareas.Wefindthatthelikelihoodofbeingpoorwasabout24percentlowerforruralfamiliesthathadatleastonememberinoff-farmactivitiesin1994andabout23percentlowerin1997(Table15).Also,inthepanelstudyofhouseholds,off-farmemploymentinfluencedconsumptiongrowthofhouseholdsstronglyandpositively.Thelabormarket,though,comprisedoftrade,small-scalemanufacturing,andtransportremainsrelativelyunimportantincomparisontoagriculturalemployment:in1994,onlyabout13percentoftotalworkdayequivalentsweredevotedtooff-farmlaboractivitiesinruralPeru.Thisisconsiderablylowerthaninothercountriesintheregion.36Thestronglinkwefindbetweenoff-farmactivitiesandwelfareimprovementsofhouseholdspointstoapotentialrolefortheseactivitiesinthefightagainstpoverty.Studiesfromothercountrieshaveshownthat,inadditiontogeneraleconomicperformance,ruraloff-farmactivitiesdependheavilyoninfrastructure,especiallyruralroads.

Table18:UrbanProblems:RankingExerciseofTwentyCommunitiesinAte,Lima,

December1997Rank#

Problem Problemin#of

communities1 water&sewerage:not

working17

2 childmalnutrition 153 streetconditions 15

bad/accidents4 violence(assaults,

domestic)14

5 houses:unfinished 146 environmentalpollution

andrelatedcontagiousdiseases

14

7 noemployment 128 distancetobasiceducation 99 nolocalcommunityhall 810 youthgangs 811 badbasichealthcare 712 insecurelandownership 613 norecreationalspace 514 vasodelecheprogramnot

wellequipped3

15 drugs,alcohol 3Source:MinistryofthePresidency(1997).

UrbanViolence.Urbanviolenceisonethebiggestpreoccupationsoftheurbanpoor.Althoughactsofpoliticalviolencehavebeencontainedsincethebeginningofthisdecade,publicconcernaboutcriminalandsocialformsofviolence-includingrobberies,armedattacks,andsexualassaults-hasrisensharplyinrecenttimes,asmirroredbytheattentiontheyreceiveinthemedia.Howimportantviolence,itsdifferentforms,anditsimpactsareforthelifeoftheurbanpopulationisshownbytheoutcomeofarankingexercise.TheMinistryofthePresidencyasked20poorneighborhoodsintheLimadistrictofAte37(withasampleofalmost40,000people)toconductneighborhoodmeetingsinwhichthemainproblemsofthepopulationwouldbeprioritized,theirmaincausesidentifiedandpossiblesolutionssuggested.Each

36SeeSaavedra(1998)andLanjouw(1998).37AteisabigdistrictinLima'seasterncone.Ithasalmost300,000

inhabitantsandaccordingtotheFONCODESpovertymap(derivedfromthecensus),abouthalfofitspopulationhasnoconnectiontowaterorsewerage,and30percentarewithout(legal)electricityconnections.Themalnutritionrateofminorsbelowtheageoffive,extrapolatedusingcensusdata,isabout30percent.Abouthalfofthehouseswereinthe'viviendaprecaria'category.Schoolassistanceratesareveryhigh(95%)andanalfabetism5.1percent.Theseindicators,aggregatedintooneindexusedbyFONCODES,rankAteasthetenthpoorestdistrictinLima(outof41).

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communitycouldspecifyasmanyproblemsasitdeemedimportant.Table18recordstheconsolidatedresultsofall20casestudies.

Violencewasoneofthemainproblemsidentifiedbythesetwentyurbancommunities.AsshowninTable18,fourteencommunitiesspecifiedassaults,robberies,anddomesticviolenceasoneoftheirlargestproblems,afterwaterandsewerage,childmalnutrition,andstreetconditions(withassociatedhighaccidentrates).38Further,youthgangsweregenerallynamedseparately,reflectingthatinadditiontotheiroftencriminalactivities,theformationofyouthgangsworriesparentsandshowsthatthesocialfabricofcommunitiesisthreatened-beitforunemploymentorotherreasons.

Thecommunitiesalsodiscussedthecausesofviolenceandpossiblesolutions.Foryouthviolence,thecausesareperceivedtobeeconomic(youthunemployment)andthelackofsupervisionandastrongcoreofacceptedbehaviorsandvalues.Proposedsolutionsarepracticalandrestrainedtowhatthecommunityitselfcando(possiblywithsomeoutsidehelp):buildingsportsfacilitiestoluretheyoungoffthestreets,organizingtrainingclassesforparents,andconductingvocationaltrainingcourses.Withrespecttodomesticviolence,allcommunitiesagreedthatthemajorreasonforfamilyviolenceisadeteriorationofrespectamongfamilymembers.Unanimously,thefourcommunitiesthatgavehighprioritytodomesticviolencesuggestedthatmandatoryclassesbeheldformalehouseholdheads-suchclasseswoulddiscussbasicfamilyvaluesandtherightsofwomenandchildren.Lastly,thecommunitiesagreedinlargepartonthecausesofrobberiesandassaults:absent(orinfrequentandirregular)policecontrolsandtoofewneighborhoodsecuritycommittees.Thecommunitiesconsequentlyproposestrengtheningsuchsecuritymeasures.

Aviolencesurvey(EncuestadeHogaressobreViolencia,ENHOVI)

wasconductedbyINEItoassesscertainactsofviolenceinLimain1997.Usingsimplepredictionmodels,wecombinedthisviolencesurveywiththeENAHO(1996)andwereabletoimputeconsumptionlevelsforeachhousehold,whichallowedustolookattheincidenceofdifferenttypesofviolencebyconsumptiondecile.39Duetothesensitivenatureofthetopic,thesurveyexcludedviolencewithinthefamily,however.

Wefindthattheoverallincidenceofviolenceisveryhighandthatcertaintypesofviolencearelinkedtopovertylevel.Overall,morethanonethirdofthepopulationinLimawasvictimtoorwitnessofaviolentactin1997.AsGraph12shows,robberies(inthestreetorhouse,orofthecar)weremoreprevalent-ascouldbeexpectedamongricherLimaresidentsbutstillsignificantforthepoor.About23percentofthelowestfourdecileswerevictimsoforwitnessestosuchviolence.Theincidenceofphysicalaggressionwassignificantly

38Theserankingswereobtainedthroughgeneralcommunitymeetings;specializedfocusgroups(e.g.bygender)couldhaveresultedindifferentresultsbutthosewerenotconducted.39Weimputedhouseholdconsumptionusingthefollowingprocedure.First,weselectedallvariableswhichwereinboththeviolencesurveyandtheEncuestaNacionaldeHogares(1996).Second,wederivedsimpleeconometricmodelsinwhichhouseholdconsumptionisafunctionofoccupationalstatusofhouseholdmembers,householdsize,accesstoservicesandeducationattainmentofhouseholdmembers.Third,weusedthesemodelstoimputehouseholdconsumption.Finally,wederivedconsumptiondecilesbyrankinghouseholdsaccordingtotheirpercapitaconsumptionlevelandusingexpansionfactorssuppliedinthesurveyasweights.

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lowerthanthatforrobberybutconcentratedamongthepoor:theriskofbeingexposedtophysicalaggressioninthepoorestdecilewasaboutdoubletheriskofthatintherichestdecile.TheINEIsurvey(1997)revealsthatinabouthalfthecasesofphysicalviolence,theperpetratorwasknowtothevictim.Finally,itisinterestingtonotethatabout90percentofallviolentactswerenotreportedtothepolice,inonequarterofallcasesbecauselackoftrustintheauthorities.

Graph12:IncidenceofViolncebyConsumptionLevel,1997,(percent)

Source:StaffestimatesbasedonENHOVI(1997)andENAHO(1996).

Graph13:SecurityFeelinginNeighborhoadsbyConsumption

Level,byConsumptiondocile,1997(percent)Source:StaffestimatesbasedonENHOV(1997)andENAHO(1996).

MirroringtherankingexerciseoftheneighborhoodcommunitiesinAte,lessthan10percentofthepoorfeltsafeintheirneighborhood.Graph13depictsthepercentageofthepopulationinLimawhostatedthattheyfeelsecureintheirneighborhood.Thesecurityfeelingisclearlylinkedtopovertylevels,withaboutfourtimesmoreLimeniosintherichestdecilefeelingsecurethaninthepoorestdecile.Thishighinsecurityfeelingoftheextremepoorlimitstheirmobilityand,withthat,boththeirsocialinteractionsandearningpossibilities.

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5.GrowthandEmploymentOneofthebiggestconcernsinthePeruvianpublicdebateonpovertyiswhethergrowthhascreatedemploymentandwhetherthishasledtopovertyreduction.Thissectionexaminesthisquestion.Itfindsthat,yes,growthoverthepastyearshasindeedcreatedemployment;about1.3millionmorepeoplewereinremuneratedemploymentin1997comparedto1994.Manyofthesenewjobsareinformalsoworkersdonothavesignedcontractsorarecoveredbyhealthorold-ageinsurance.Also,productivitydoesnotseemtobeincreasingandconsequently,realwagesareflatatbest.Themajorimpactofgrowthonpovertyreductionhasthusbeenthroughemploymentcreationandnotthroughrealwageincreases.

Thesectionstartswithgenerallabormarkettrendsandthenanalyzesthelinksamonggrowth,poverty,andemployment.Wethenpresentanumberofdifferentsimulationsoffuturepovertyreductionpossibilities,takingintoaccountbothpossiblevaryingregionalandsectoralgrowthpatterns.

LaborMarketTrends

Intheyearssince1994,1.3millionnewjobswerecreatedinPeru.Peoplefindingjobswereaverysmallpercentageoftheunemployedbutmanymorewerenewcomerstothelabormarket.TheparticipationrateinPeru,alreadyontherisesincethebeginningofthedecade,hasagainstronglyincreased.Table19showsthatparticipationratesformenincreasedby2.3percentandforwomenbyalmost7percentbetween1994and1997.

Table19:LaborForceParticipationRates,

1994and1997male female

1994 1997 1994 1997Urban 75.6 79.9 45.2 53.1Rural 91.4 91.3 64.9 72.9Total 80.7 83.0 51.2 59.0Source:StaffestimatesbasedonENNIV(1994,1997)

Newjobswerecreatedmainlyintheinformalurbansectoroftheeconomy.Usingalegalisticdefinitionofformality,40theincreaseinformalsectoremploymentwasslightlylessthanhalfamillionwhileinformalemploymentgrewbymorethan800,000(Table20).However,theterminformalitygenerallyreferstotheurbansectoronlysinceruralemployment-

Table20:RemuneratedJobCreation,byFormalandInformalSector,19941997

('000)formal informal TOTAL

Urban 430 585 1015Rural 45 235 280Total 475 820 1295Source:StaffestimatesbasedonENNNIV,(1994,1997).

40Thelegalisticdefinitiondefinestheformallabormarketascomprisingallwageearnersortheself-employedwhopaytaxes,areinsuredwiththesocialsecurityinstituteIPSS,haveasignedcontract,haverightstovacation,orbelongtoaunion.SeeSaavedraandChong(1999).

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small-scaleagriculture-isbyitsverynatureinformal.Butevenfortheurbansectoralone,themajorityofjobswerecreatedininformalemployment,andthatshareoftheinformalsectorincreasedslightlysince1994.Aspointedoutabove,informalityshouldnotbeequatedwithbadjobsassuchactivitiescanoffermanyofthepoorarouteoutofpoverty.

GrowthPattern,PovertyReduction,andSectorEmploymentGrowth

Ouranalysisfindsthatemploymentgrowthwascloselylinkedtopovertyreduction.Table21looksatseverepovertyratesandemploymentgrowthforthedifferentsectorsinthePeruvianeconomy.41Ascanbeseen,thethreesectorswiththehighestemploymentgrowthrates(construction,tradeandcommerce,andservices)arealsothethreesectorsthatachievedthehighestpercentagedecreaseinpoverty.Muchofthisemploymentgrowthprovidedfamilieswithmorehoursofworkorasecondsourceofincome.Similarly,agricultureandmining/manufacturinghadthelowestemploymentgrowthratesandalsoshowedthelowestpercentagereductionintheseverepovertyrate.

Sectorgrowthratesandemploymentcreationareconnected.AsTable21reports

Table21:PovertyReductionbySectorandGrowthRates,19941997Sectors Severe

Poverty1994Rate1997

Perc.ChangeSev.Pov.Rate

19941997

EmploymentGrowth19941997

RealGDPGrowth(formalsector)19941997

DistributionofSeverePoor1997

(1) (2) (3) (4) (5) (6)Agricultural&forestry

31.8 26.4 -17.0 10.3 23.4 (30.4)

Construction 25.2 17.4 -31.0 63.9 33.8 (7.2)Transport&communnications

11.8 10.2 -13.0 18.0 n.a. (7.8)

Tradeandcommerce

13.8 8.6 -37.5 43.9 22.8 (18.4)

Mining,petrol&manufacturing

9.2 8.4 -8.5 7.9 13.7 (12.7)

Services 11.9 8.8 -26.0 21.6 8.4 (23.5)TOTALCOUNTRY

18.8 14.8 -21.0 19.0 18.1 100

Source:StaffestimatesbasedonENNIV(1997).Allhouseholdshavebeenassignedaprimarysector,e.g.,thesectorofthemainincomeearner.RealGDPgrowthratesfromCentralBankofPeru(1998).

(column4),thepushsectorsinPeruoverthelastyearswereagriculture,construction,andtrade.However,theserealgrowthratescaptureonlytheoutputofformalenterprisesanddonotnecessarilyaccountformanyinformaleconomicactivities;thus,strictlyspeaking,thegrowthandemploymentdatacannotbedirectlycompared.Nevertheless,thetwocanbethoughtofascloselylinked-ifformalsectorgrowthishighinaspecificsector,supportingor

41Tolinksectorsoftheeconomyandpoverty,weassignahouseholdtoasectorbasedontheprimaryoccupationofthehouseholdhead.Thisleavesonlyabout80householdsunaccountedfor(non-activehouseholdheads),andweneglecttheseinthetableandcalculations.

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parallelinformalenterprisesshouldalsorealizeanupswing.Onfacevalue,Peru'sgrowthpatternwaspro-pooroverthetimeperiodbecauseitwasdrivenbythesectorsinwhichseverepovertyrateswerehighest(columns1and2).

Inconstructionandtraderealgrowthtranslatedintoemploymentgrowthandpovertyreduction.ButoneofthekeyfactorsexplaininginequalityandpovertydevelopmentsoverthepastyearsinPeruisthattheimpressiveagriculturalgrowthratesdidnottranslatefullyintoemploymentcreation.Realgrowthratesinthatsectorareestimatedat23percentoverthe19941997period(column5inTable21);afterconstruction,agricultureisthebestperformingsector.Growthhasespeciallybeenstronginnon-traditionalexports.Agriculturalproductivitywasseriouslydepressedatthebeginningofthe1990s,soonecanexpectgrowthtobegeneratedinlargepartbytheexistingworkforceworkinglongerhours.Thiswouldbeonepossibleexplanationfortherelativelylowgrowthelasticityofemploymentgenerationinagriculture.Thisexplains,toalargeextent,thegrowingregionalurban-ruralinequalityinPeruaswellasslowersocialprogressinruralPeru.

GrowthandPovertyReduction:Simulations

Anumberofsimulationsshowhowimportantcontinuedgrowthisforpovertyreductionbutalsohowunequal,anti-poorgrowthcanreduceoreradicatethepotentialbenefitsofeconomicexpansion.

GrowthwillremainthebackboneofanysuccessfulpovertyreductionstrategyinPeru.Thesimulationsweemployedwereverysimpleanddistributedthegainsfromgrowth(higherincomeandconsumption)insocietyusingthehouseholdsurveyfrom1997asthebasictool.42Forexample,thesimulationsdonottakeintoaccountthatproductivitydevelopmentsandhencethelinkbetweengrowthandemployment

creationwillvarybysector.Further,wealsoabstractfrommobilityacrosssectors.Thesimulationsdoshow,however,thatthepatternanddistributionofincomegainsmatterforpovertyreduction.

Graph42:ReductioninSeverePovertyRateforVarying

GrowthRates,percentagechange,fiveyearsimulationSource:StaffestimatesbasedonENNIV(1997).

Graph14showsthatPerucouldreduceseverepovertybyafurther25percentinthecomingfiveyearsifitweretoachievearealpercapitagrowthrateof3percent.Highergrowthrateswouldmeanfasterpercentreductionofseverepoverty-a7percentrealpercapitagrowthratewouldreduceseverepovertybyhalfinfiveyears.However,aswehaveseenfrom1994to1997,inequalitycannotbeassumedtobeconstant.Ifthetrendofincreasinginequalityweretocontinueand

42Thisassumesthatincomes(andconsumption)arerelatedtotheoverallgrowthrateintheeconomythroughproductivity(andwage)increasesorthroughthecreationofnewemploymentforsecondaryworkoradditionalincomeearners.

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thesocietyweretobecomeconsiderablymoreunequal,growthmightnottranslateintopovertyreductionatall:iftherichest20percentofthepopulationincreasetheirconsumptionby10percentwhiletheeconomygrowsat3percent,therichwouldsimplyreapallthebenefitsfromgrowth.Severepovertywouldnotfall.Inthereversecase,ifinequalityfallsandthepoorest40percentofthepopulationincreasesitsshareoftotalconsumptionfrom20to25percent,severepovertycouldbereducedbymorethan60percent.

Table22:SimulationofSeverePovertyReduction:DifferentAssumptionAboutInequality(realgrowth

rateof3percentfor5years)Simulation SeverePovertyReduction

(percent)Inequalityconstant

-23.0

Inequalityincrease1

0

Inequalitydecrease2

-62.0

Source:StaffestimatesbasedonENNIV(1997).1anincreaseininequalityimpliesthattherichest20percentofthepopulationincreasetheirshareoftotalconsumptionfrom43to50percent.2adecreaseininequalitymeansherethatthepoorest40percentofthepopulationincreasetheirshareoftotalconsumptionfrom20to25percent.

Thepatternofgrowthmattersforpovertyreduction.Again,thesesimulationsarehighlystylizedastheyassumethatsectorgrowthtranslatesdirectlyintogrowthofhouseholdconsumptionviaadditionalemploymentandrealwagechanges(andwesawabovethatfortheagriculturalsectorthisrelationshipdidnotholdfrom1994to1997).Further,thesesimulationsassumenofeedbackeffects-for

example,thatgrowthinexportsectorswouldleadtotechnologicalspillovers,asisgenerallyfound.However,thesimulationsdoprovideaninterestingcomparisonofhowdifferentpatternsofgrowthmatterforthepoor.Table23recapsthefindings.Wefindthatifgrowthispro-poor,thatis,concentratedinagricultureandconstruction,severepovertywouldbereducedbymorethanhalfinfiveyearswithanoverallannualpercapitagrowthinallsectorsof3percent.Ontheotherhand,ifgrowthweretobeconcentratedinservices,theimpactonseverepovertywouldbeonly25percent.Whilegrowthshouldnotbeartificiallytiltedtowardsthepro-poorsectors,investmentinthesesectorswilldependonacontinuationofpoliciesthatdonotdiscriminateagainstthem.

Table23:SimulationofSeverePovertyReduction:DifferentSectoralGrowthRates(realgrowthrateof3

percentforfiveyears)Simulation Sectors Severe

PovertyReduction

Growthofhigh-povertysectors

agricultural,construction

-49.2

Growthofmedium-povertysectors

mining,petroleum,manufacturing,commun.

-27.7

Growthoflow-povertysectors

services -24.3

Source:StaffEstimatesbasedonENNIV1997.Thesimulationsassumethatthegrowthrateofhighgrowthsectorsis6percentwithallothersectorsgrowingequallyattheresidualgrowthrate.

Closelylinkedtothisstrongimpactofthesectorgrowthistheimpactofdifferentregionalpatternsofdevelopment.Severepovertyreductionwouldbestrongestiftheruralsectors(withallon-farmagriculturalandoff-farmactivities)weretocarryPeruvianeconomic

progressinthecomingyears.Table24showstheresultsforthis

Table24:SimulationofSeverePovertyReduction:DifferentRegionalGrowthRates(real

growthrateof3percentforfiveyears)Simulation SeverePovertyReductionLima -22.3Otherurbanareas -26.4Ruralareas -47.0Source:StaffestimatesbasedonENNIV(1997).Thesimulationsassumethatthegrowthrateofhighgrowthregionis6percentwithallotherregionsgrowingequallyat3percent.

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calculation.Theseverepovertydeclinewouldbesimilartotheoneobservedwithagricultureandconstructiongrowth:almost50percent.IfLimaweretocontinueitsroleastheengineofgrowth,however,severepovertyreductioncouldbemuchsmaller-arounda22percentdecline.

TheTaskAhead:RaisingProductivityandRealIncomes.

Graph15:MetropolitanLima:MonthlyRealIncomeofInformalWorkers,19941997

Graph16:MetropolitanLima:MonthlyRealIncomeofFormalWorker19941996

Source:EncuestadeHogaresdelMTPS1Traditionaldefinition

Oneofthemajortasksinthecomingyearsistoraiseproductivityand,withit,realincomes.Untilnow,employmentgenerationhasnotbeenaccompaniedbyrealincomeincreases(Graphs15and16).ForLima,graphs15and16showrealincomedevelopmentsinboththeformalandinformalsectorssince1986.Ascanbeseen,hyperinflationcontractedrealwageincomeenormouslyin1990andtherecoveryperiodoftheeconomywenthandinhandwithincreasingrealwages.However,withveryfewexceptions,realincomeshaveremainedflatsince1991andinsomesectorsevenshowdecliningtrends.Thesetrendsarematchedverycloselybyoverallproductivitydevelopmentsinthecountry.43Intermsoflevels,realwagesremain-independentofsectorandtypeofoccupation-belowtheirlevelof12yearsago.ThePeruvianexperienceofrealincomeandproductivitydevelopmentsisnotatypicalforcountrieshavingundergonestructuralreforms.InBrazil,wagesincreasedonlyslightlysincetheliberalizationin1991.InChile,realwageswerebasicallystagnantforabout10yearsaftertherecessionof1982andthemarket-orientedreforms.Risinglaborforceparticipationincreaseslaborsupplyanddampenswageincreases.Nevertheless,themorethegovernmentsupportstheprivatesectortoraiseproductivity,thequickerwillrealincomechangesfilterthroughtheeconomy:supportingpublicinfrastructureinvestment,trainingsupport,andeducationofthenextgenerationofwage-earnerscanallcontributetothis.

43Saavedra(1998).

Page37

6SocialExpenditures-WhatandforWhom?Tocomplementtheanalysisofpovertycomparisons,wehaveonemajorquestionstilltoanswer:whatwastheroleofpublicprogramsinpovertyreduction?Didtheyhelptoreducepoverty?Orweretheyintheendoflittlevaluetotherecipients?Thissectionwillpresentavailablematerialtoanswerthisquestion-butwewillfallshortofestablishingaclearlinkbetweenpublicprogramsandpovertyreduction.Toshedlightonthistopic,wewouldneeddetailedinformationonhouseholdsbeforeandafteranintervention,e.g.thewell-beingofahouseholdbeforeandafteritreceivesnutritionalaidthroughtheGlassofMilkprogram.Andwewouldneedacontrolgroup,i.e.,familiesthataresimilarintheircharacteristicsbutdidnotbenefitfromthesameprogram.Wehadhopedthatthepaneldata,containinginformationaboutidenticalhouseholdsovertime,wouldserveforthisanalysis,butunfortunately,wewerenotabletoclearlyestablishwhichspecificprogramshadwhatkindofeffectonhouseholdwelfare,partlybecausethesamplesizewasseverelylimited.Theonlyclearresultweobtained,asreportedearlier,concernedtheprovisionofpublicservicesinwater,sanitation,andelectricity:theseraisedfamilies'welfareand,inaddition,hadabundlingeffect-threeserviceshavingmorethanthreetimestheeffectofoneservice.However,sinceliterallydozensofprogramsfinancethistypeofinfrastructurewecouldnotdistinguishwhichonesweresuccessfulandwhichoneswerenot.

Whatwecandointhissection,though,aretwothings:first,takeanaggregateviewofsocialexpendituresandanti-povertyprograms,andassesswhomtheybenefitedandhowmanypeopletheyreached-withoutjudgingwhethertheyweresuccessfulornot.Forthisanalysis

weusedtheEncuestaNacionaldeHogares(1996)fromtheStatisticalInstituteofPeru(INEI),asurveyconsiderablylarger(20,000households)thanthatoftheInstitutoCuánto.Second,wecananalyzetheshort-termimpactofdirecttransferprogramsonpoverty.

SocialExpendituresin1996

Beforepresentingourresultsonthedistributionofaggregatesocialexpenditures,onecautiousremarkneedstobemade:figurespresentedhererelatetotheaverageincidenceofprogramexpenditures,i.e.,whatpercentagereachedwhichgroupinthepopulation.Basingpolicydecisionsonsuchanaverageincidencemightbemisleadingasthedistributionofmarginalexpendituresmightbeverydifferent.Orinotherwords,aprogrammightbenefitlargelythenon-poorinsocietyatagivenpointintime.However,theadditionalprogrambudgetmightgodirectlytothepoor,soapolicydecisionontheaverageperformancemightnotbewise.Suchagapbetweenthedistributionofaverageandadditionalexpendituresislikelytobehighforprogramsthathavealargepartoftheircurrentbudgetlinkedtopastinvestments(e.g.educationorhealthprograms).Thedifferencewillnotbeverypronouncedforprogramsthatfinanceshort-maturationprojectsandthenmoveontodifferentsites,asiscommonunderthesocialinvestmentfunds.

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AggregateDistribution.Weexamineexpendituresintheeducationandhealthsectors,inhousingandinfrastructureprograms,andinanumberofspecializedantipovertyprograms.44Together,theseprogramsaccountedforatotalexpenditureof7.6billionsoles,orroughly40percentofthetotalpublicbudget.Ofthat,about55percentwasintheeducationsector,25percentinhealth,12percentinhousing,andbasicinfrastructureprograms,and8percentintheantipovertyprograms.

Table25:BudgetExaminedinAnalysis(1996),billionsoles

Education 4.1Health 1.9Housing&Infrastructure 1.0AntiPovertyPrograms 0.6Total 7.6Source:ComisiondePresupuestodelCongreson;Saavedra(1998)

Lookingatthegeneraldistributionofexpenditures,thefirstobservationisthat,in1996,theywentmostlytotheurbanareas.Weestimatethatabout70percentoftheexaminedexpenditurewenttourbanPeruandthisislikelytobeanunderestimate,sinceweassume-asiscommoninincidenceanalyses-thatthepercapitabenefittobeneficiariesisequalacrossthecountry.Itisalltoowellknown,however,thatperbeneficiaryexpendituresinhealthandeducationaremuchlowerinruralareas(seeGraph11above).Table26reportsthatonlyoneprogramorlineofactivitytargetedthemajorityofitsexpendituretoruralareasin1996:thesocialfundFONCODES,whichhadformulatedanexplicitstrategytotargettheruralpooratthebeginningoftheyear.ItislikelythatFONCODESincreaseditstotalbudgetallocationtoruralareasin1997evenfurther,givenitstargetingstrategy.Itisthereforeaclearexceptiontothelargelyurban

biasofothersocialprograms.

Table26:Rural/UrbanDistributionofGovernmentExpenditures,1996

sector shareofexp.receivedbyrural

residentsEducation&healthsectors:Basiceducation education 47Secondaryeducation

education 19

Universityeducation

education 6

Basichealth health 50Hospitalcare health 16byprograms:FONCODES various 68PRONAA nutrition 44INABIF children 2FONAVI elec&

water20

ENACE housing 10BanMat housing 11INFES education 16Total 30memo:Shareofpoorinrural(1997) 47Shareofseverepoorinrural(1997)

58

Source:StaffestimatesbasedonENAHO(1996).

44TheantipovertyprogramsincludeFONCODES,PRONAA,COOPOP,INABIFandINFES.ThehousingandinfrastructureprogramsincludeENACE,BanMatandUte-FONAVI.

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AggregateSocialExpendituresDistribution.Examiningthetotalbudgetof7.6billionsolesconsideredhere,expendituresweremildlytiltedtowardthebetter-offinsociety.Onlyabout17percentofexpenditureswenttothepoorest20percent(Table27).Itappearsthatifexpendituredistributionwaslargelydrivenbythepopulationdistributionratherthanbypovertylevel,thiswasalreadyobservedabovewhenwelookedatthedistributionoftotalexpendituresbyurbanandruralarea-there,aswellasbypovertygroup,wecannot(onsuchanaggregatelevel)detectthetargetingofexpenditurestotheweakestinsociety.Giventhatthebudgetwelookathereisthesocialandanti-povertybudget,thisisadisappointingresult.

Table27:AggregateDistributionofSocialExpenditures

quintile shareoftotalexpenditure1(poorest) 16.62 18.63 21.24 22.45(wealthiest) 21.1Source:StaffEstimatesbasedonENAHO(1996).

Graph17:

EducationExpenditurebyPopulationQuintile,1996Source:ENNAHO(1996).

Graph18:HealthExpenditurebyPopulationQuintile,1996

Source:ENNAHO(1996),INEI.

EducationandHealthExpenditureDistribution.Asobservedinmanycountries,Peruvianexpendituresinbasiceducationandbasichealthwereprogressivein1996,whilemosthigher-levelspendingwenttothebetter-offinsociety.Graphs17and18presenteducationandhealthLorenzcurvesfor1996withthehorizontalaxisrepresentingthepopulationdistributionandtheverticalaxisthedistributionofexpenditures.Ascanbeseenprimaryeducationexpenditureswereconsiderablymoreprogressivethansecondaryandhighereducationexpenditures.Forthehighereducationexpenditures,abouthalfoftotalexpendituressupportedtherichest20percentinsociety.Similarly,hospitalcare(bothambulatoryandstationary)wasconsiderablymoreregressivethanprimaryhealthcare-30percentofresourceswenttothetoppopulationquintile.

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CoverageandTargetingRates.Whileeducationandhealthprograms,bytheirverynatureare(orshouldbe)universalprograms,theotherprogramsandprojectslookedathereintendtoreachspecificgroupsinsociety.FONCODES,forexample,aimedatreachingtheextremepoorintheruralareasin1996,andPRONAAwantedtoreachpoorfamilieswithmalnourishedchildren.

Toassesshowwelltheseprogramsdidin1996,wewanttomeasuretheirsuccessusingtwoindicators.Thefirstisthecoveragerate.Thisissimplythepercentageofthepoorpopulationreached.Thesecondisthetargetingperformance,i.e.,thepercentageoftotalexpendituresthatactuallywenttotheintendedbeneficiariesanddidnotescapetobetter-offgroups.Itshouldbenoted,though,thatseveraloftheprogramsconsideredhere,especiallythehousingandbasicinfrastructureprograms,didnothavethearticulatedaimofreachingthepoorinsociety.Nevertheless,wewanttoholdthemtotheabovecriteria.

Graph19:CoverageandTargetinginPeru,1996

WefindthatFONCODESandPRONAAhavethebestrecordinreachingtheirbeneficiariesandtargetingtheirexpenditures.Graph19

showsbothoftheseindicatorstogether.Againstthehorizontalaxisweplotthecoveragerate,i.e.,thepercentageofthepoorest40percentreached.Againstthehorizontalaxiswemeasuretheconcentrationofexpendituresinthesametwoquintiles-ourtargetingindicator.Aprogramthatreachesasubstantialportionofthepopulation(i.e.,hasahighcoveragerate)andatthesametimemanagestoconcentrateitsresourcesinthepooresttwoquintileswouldgetanentryintheupperrightcorner.Ontheotherhand,programsthatreachfewofthepoorandconcentrateonlyasmallpercentageoftheirtotalresourcesonthemwouldendupinthelowerleft-handcorner.Ascanbeseeninthegraph,coverageratesformostprogramswererelativelysmall-mostlybelow5percent.Andconcentrationshareswerealsorelativelylow;mostprogramsspentlessthan40percentinthebottomtwoquintiles.ThesocialfundFONCODESandPRONAAwereexceptions-bothofthemshowaprogressivedistributionofexpendituresandarelativelylargecoveragerate(seeBox2foranevaluationofnutritionprograms).

Page41Box2:NutritionProgramsinPeru--TargetingRates,CoverageRates,andBenefitDistributionMalnutritionPrograms:DistributionofRealProgramBenefits,1997group coverage monetarybenefitmalnutr.&poor 66.3 38.0malnour.&non-poor 43.3 22.3non-malnuri&poor 47.0 15.9non-malnur.&non-poor

32.7 23.8

(100)Source:StaffEstimatesbasedonENNIV(1997).Distributionofmalnourishedchildrenanddistributionofnutritiontransfers,1997

distributionofthemalnourished

distributionofprogramexp.

Lima 8.9 31.6Urb.Coast 6. 8.8Rur.Coast 5.1 9.6Urb.Sierra 7.7 5.3Rur.Sierra 51.3 31.9Urb.Jungle 5.1 4.4Rur.Jungle 15.0 8.4

(100) (100)Source:StaffEstimatesbasedonENNIV(1997).Coverageratesofthenutritionalprogramsare,byinternationalstandards,veryhigh.In1997,about60percentofpoorhouseholdsreceivedsomenutritionalbenefitfromoneofthemanynutritionalprograms.ThebiggestoftheseprogramsaretheGlassofMilkprogram(VasodeLeche,MinistryofFinance,workingthroughmunicipalities),theSchoolBreakfastProgram(administeredbyFONCODES),andthelocalsoupkitchens(ComedoresPopulares,financedlargelybyPRONAA).Theadjacenttablebreaksthehouseholdsinthepopulationintofourdifferentgroupsbypovertyandmalnutritionlevels(householdswithatleastonemalnourishedchildfallinthemalnourishedcategory).Resultsshowrelativelygoodtargetingandhighcoverageratesofnutritionprogramsevaluatedjointly,withthepoorhouseholdswithatleastonemalnourishedinfantshowingacoveragerateof

66percent.Thenon-poorhouseholdswithwell-fedinfantsshowamuchlowercoveragerate,of23.7percent.However,theprogressivenessofthistransferisconsiderablysmallerifwecalculatethenetmonetarytransferequivalent(takingintoaccountfrequencyandquantityofthetransfer).Takentogether,leakageofthenutritionalprograms(i.e.,transfersneithertothepoornorthehouseholdswithmalnourishedchildren)isabout24percent.Onaregionalbasis,theruralSierrareceivesconsiderablylessintransfersin1997thanitshouldgiventhatabout51percentofallmalnourishedchildrenlivethere.Limareceivesamuchlargersharethanitwouldwereexpendituresdistributedinaccordancewiththegeographicalprevalenceofmalnutrition.Ascanbeseenfromthecoveragerates,Peru'snutritionprogramsareverylarge.AccordingtotheBudgetCommission,spendingonthenutritionalprogramsofPRONAA,theGlassofMilkprogram,oftheMinistryofEducation,andFONCODESaloneincreasedfromUS$190millionin1994toaboutUS$250millionin1997.Buttherearemanymoreprograms,administeredcentrallyandbymunicipalities;forexample,PACFO(ProgramadeComplementationAlimentariaparaGruposenMayorRiesgo;SupplementaryFeedingProgramforHighRiskGroups)intheMinistryofHealthwhichtargetsthe5poorestdepartmentsinthecentralSierra.OneofthebiggestproblemsinthesectoristhattheMinistryofWomenandHumanDevelopmentisformallyresponsiblefordiagnosingthenutritionsituationandestablishingnutritionpolicies,programobjectives,implementationnorms,andstandards.ButtheMinistryhasonlyverylimitedauthorityovermanypoliciesandprograms,someofwhichhavenonutritionalobjectivespersebutarerathergearedtowardincomegenerationorschoolattendance.

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ReasonsforPoorProgramTargeting.Manystudieshaveanalyzedthequitemeagercoverageandtargetingperformanceofthesocialprogramsdescribedinthissection.Thereasonsfoundare:(a)littleuseof(existing)povertymaps(exceptforFONCODESandPRONAA);(b)anurbantiltinexpendituredistribution,whichmeansthatmanyoftheextremelypoorinruralareascannotbereached;and(c)criteriaforprogramaccesswhichexcludemanyofthepoor(especiallyinthehousingcreditprogramsENACEandBanmat).Forbothnutritionprogramsandprogramsofselectedministries,suchastheMinistryofthePresidency,ithasbeenrepeatedlyobservedthatmanyprogramsoverlapinfunctions,arenotcentrallycoordinatedandaresubjecttoarbitraryexpendituredecisions.45Targetingmaps,ifused,havebeenfoundusefulforexpenditureallocation.However,themapmostwidelyusedbyFONCODESwasfoundtocontainaseriouserror.Themapisbasedontheconstructionofapovertyindexwhichisitselfanaggregateofseveralindicators.Asaconsequenceoftheaggregationprocedure,malnutritionwhichwassupposedtohavethehighestweightinthepovertyindexwasassignedamuchlowerimportance-15percentinsteadof50percentwhereastherooftypeofhouseswasweightedwith40percentinsteadoftheplanned7percent(WorldBank,1996).Similarly,recentanalyticalworkalsoquestionsthepovertymapnowusedbytheMinistryofthePresidencyinitsLuchaContralaPobreza(FightAgainstPovertyProgram).46Becausethismapusesthenumberofthepoorperdistrictasoneofthekeyvariablesdeterminingexpenditureallocationinsteadofthepovertyrateorpovertydepth,itheavilytiltsresourcestolargerdistrictsinurbanareas.Infact,thepercapitaexpendituredistributionunderthisschemeisfoundtobeworsethanifresourceswereallocatedonapurelypopulationbasis.

PovertyImpactofDirectTransfers

Unlikethebasicandsocialservicesprograms,directtransferprogramsaregearedtohelppoorfamiliesintheshortrun.InPeru,theseprogramscomprisemainlythemanylargenutritionalprograms,butalsoincludetheemploymentprograms,e.g.ofFONCODES.Further,wecanalsocountpensionpaymentsfromtheNationalSecurityInstituteasapublictransfer.Howimportantarethesepublictransfersforfamilies?Andhowimportantarethesepublictransferscomparedtoprivatetransfersfromfriends,neighbors,andfamilymembers?

Weanalyzetheeffectoftransfersbyestimatingtheimpacttheyhaveonpovertyrates.Inreality,transfersmightnotincreasehouseholdwelfareintheshortrunforallfamilies.Forexample,iffooddonationsreplacethepurchaseoffood,familyincomemightbesaved,usedtorepaycredit,orspentinawaythatisnotbeneficialtothepoorestinthefamily.However,thisexerciseassumesthatalltransfersreceivedhavebeenusedintheirfullamounttoincreasehouseholdconsumption.Sincewewanttocomparepublicwithprivatetransfers,wemakethesameassumptionforfamilyaid,privatepensions,andremittancesfromhomeorabroad.Publictransfersheredonotincludeeducationandhealthexpendituresorbasicandproductiveserviceinvestments.

45See,forexample,Homedes(1996)andWorldBank(1996)46SeeSchady(1998).

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Wefindthattotalpublictransfershavehypotheticallyamuchlowerimpactonpovertythanprivatetransfers.Table28examinestheimpactofanumberofdifferenttransfersonpovertyandextremepoverty.Byfarthemostimportanttransferforthepoorandextremelypooralikearenotpublictransfersbutprivatenationaltransfersfollowedbyprivatepensionsandemployerbenefits.Foodaidisthemostimportantpublictransferandhasaquitesignificantimpactonseverepovertyintheruralareasbutislesssignificantinurbanareas.

Table28:ImpactofPrivateandPublicTransfersonPovertyandSeverePoverty,1997(percentageImpacton

povertyRatefromDifferentTypesofTransfers)povertyrate

severepovertyrate

urbanrural urban ruralfoodaid -1.2 -1.7 -0.9 -3.0otherpublictransfer -0.3 -0.3 -0.1 -0.5publicpension -0.1 -0.1 -0.2 -0.1privatepensionoremployerbenefit

-4.6 -1.3 -3.5 -1.3

privatetransfers,national -4.3 -2.7 -3.5 -3.5privatetransfers,international -1.1 -0.1 -0.8 -0.1allpubliccombined -1.4 -2.4 -1.2 -3.6allprivatecombined -9.6 -3.9 -8.2 -5.1Source:StaffestimatesbasedonENNIV(1997).

Page44

7.Institutions-FromIndividualSectorStrategiestoaConsistentandBroad-BasedAnti-PovertyFocusThisreportdoesnotprovidedetailedrecommendationsastohowPerucanmakefurtherandeffectiveinroadsagainstpoverty.Suchspecificpolicyrecommendationshavebeenandwillbemadebyspecializedstudies.Thepurposeofthisreporthasbeentotakeamoreglobal,aggregateviewofsocialprogressovertheyears1994through1997,basedonlargelyevidenceofthedistributionofpublicinvestmentandsocialprograms.Thissection,therefore,takesalookatsocialpolicyformulationinPeruatamoremacrolevel.

CurrentSocialPolicyFormulation.Today,themultitudeofsocialpolicyprogramsoperatelargelyindependently,trytoreachtheirbeneficiariesthroughdifferentmeans,andlackstringentevaluation.Expendituresofmanyoftheseprograms,althoughwellintentioned,areoftenisolatedinnature,anddonotreachthepoorestinsociety.TheMinistryofthePresidencyalonehassixprogramsintheeducationsector-inadditiontoallofthoseoftheMinistryofEducation.ThemanynutritionprogramsareadministeredbytheministriesofFinance(VasodeLeche),WomenandHumanDevelopment(PRONAA),Health(BasicHealthProject,PACFO),EducationandtheMinistryofthePresidency(FONCODES).TheInterministerialCouncilonSocialAffairs(CIAS)hastheresponsibilitytoensuresmoothinterministerialinformationflowandguidesocialpolicydevelopment.Recently,CIAShasassumedamoreactiveroleinsettingtechnicalstandardsandofferingtechnicalassistancetolineministries.Itstilloperateswithoutclearmandateandresources,however.

ConflictingDecrees.Theneedfortheempowermentofonecentralsocialpolicyunitbecomesquiteapparentifwelookattwoimportantrecentpresidentialdecrees.Thefirstdecree(012-97-PCMofApril1,1997)makesthePresidencyoftheCouncilofMinisters,andwithitthesocialpolicycoordinationcouncil(CIAS),responsibleforcoordinatingandimprovingtheallocationofsocialexpendituresamongagenciesandministries.Theseconddecree(030-97-PCMofJune201997)officiallyadoptedthetargetingandcoordinationstrategyoftheLuchaContraLaPobreza,whichwasdevelopedandismanagedbytheMinistryofthePresidency.Thedecreecalledforthewidespreadapplicationofthestrategybythewholepublicsector,making-defacto-theMinistryofthePresidencyresponsibleforsocialpolicycoordination.

InstitutionsMatter.WebelievethatoneofthemostpressingneedsinthefightagainstpovertyinPeruisinstitutionalreform,whichisapreconditionforachievingamuchbiggerimpactwithavailablefunds.ArecentstudyofLatinAmericancountries,BeyondtheWashingtonConsensus:InstitutionsMatter47,showsthatthequalityofinstitutionshaveasignificantpositiveinfluenceonbotheconomicgrowthandpovertyreduction.Thestudydescribedthedecision-

47BurkiandPerry(1997).

Page45

makingprocessinPeruasinformal,i.e.,thedejuresystemisinrealitymostlyovetakenbyaverydifferentdefacto,orinformal,system.OneofthekeycharacteristicsofsuchaninformalsystemisaparallelorganizationalstructureinPeru(especiallyofkeyautonomousagencies),substantiallyby-passingthecabinetandministerialstructure.

WebelievethatoneofthemostpressingneedsinthefightagainstpovertyinPeruisinstitutionalreform,whichisapreconditionforachievingamuchbiggerimpactwithavailablefunds.First,economicandsocialpolicymakingwouldneedtobemorecloselyintegrated,informedbysoundtechnicalanalysisandadvice.Manydifferentpovertymapsandtargetingmechanismscurrentlyemployedneedtobeharmonized,sincepovertyisreducedmosteffectivelyifinterventionsareprovidedjointlyandinacoordinatedmanner.InPeru,conflictingdecreesempoweringtheMinistryofthePresidencyandCIAScurrentlyexist,butneitheroftheinstitutionshastruepowerormanpower.

Box3:Multi-SectorSocialPolicyFormulationinBrazil:TheComunidadeSolidaria

Brazil'sComunidadeSolidaria(CS)constitutesadirectlinkbetweenGovernmentandsociety.Itstaskistoidentifyandaddresscross-sectorsocialproblemsoutsidethesphereoftheFederalGovernmentbutlinkedtoitspolicymakingandprogrammechanisms.TheConsultativeCouncilofCSiscomprisedof11ministries,theExecutiveSecretariatoftheCS,and21representativesfromcivilsocietyincludingbusiness,NGOs,andvoluntaryorganizations.Itsaimistomobilizesocialefforts,implementinnovativeprojectsatlocallevels,andidentifysocialpriorities.TheExecutiveSecretariatoftheCSislinkedtotheCivilAffairsOfficeofthePresidentoftheRepublic,with

representativesfromsectorministries,provincesandmunicipalities,andcivilsociety.ConsultationsbetweenlocalorganizationsandmunicipalandfederalgovernmentshaveledtotheformulationofaBasicAgenda,whichconstitutesanactionplanforlocalanti-povertyprograms.

FundsprovidedtoBasicAgendasocialprogramsareintheformofperiodictransfersfromministriesandfederalbodiestostateandmunicipalgovernments.TransfershavegrownfromR$980millionin1995toR$2.5billionin1997,andarepredictedtoincreasetoR$2.9billionin1998.MostfundsaredesignatedforthepoorestregionsinBrazilacrosssocialsectors.Thetotalnumberofmunicipalitiesparticipatinghasalsoincreasedsignificantly,from302in1995to1,368in1997.

Closelylinkedtotheabove,pro-poorpoliciesrequiregoodtargetingandthoroughevaluation.ManydifferentpovertymapsandtargetingmechanismsarecurrentlyusedinPeruandthesecanbeharmonized.However,programplanningandmonitoringgobeyondtheneedfortargetingandprioritization.Theyinvolvepolicymakersbeingabletoassesswhetheracertaininterventiondidindeedhelpornot.Anditalsoimpliesthatpolicymakersandtechniciansareabletoassesshowchangesinprogramnatureandhowchangesinexpendituresaredistributedandwhateffecttheyhave.

Page46

Graph20:TargetingofSocialPrograms:(percentofExpenditureperquintile)

Source:ENNAHO(1997)

Third,centralcoordinationcangohandinhandwithdecentralizedexecutionthatincludesotherpartnersinthefightagainstpoverty.ExamplesfromotherLatinAmericancountriesshowthatprivate-voluntary-publicpartnershipsinpovertyreductionatthelocallevelcanbeextremelysuccessful(Box3).48Onereasonsuchpartnershipsaresuccessfulisthateachorganizationbringsitscomparativeadvantagetothetable:centralgovernmentbringsfinancingandorganization;municipalgovernmentbringsadministrativeandlocalknowledge;NGOsandcommunity-basedorganizationsofferdirectunderstandingof(andlinkto)problemsofthepoor.INEI'sEncuestaNacionaldeHogares(1996)showsthatNGO-administeredprogramshaveasignificantlybettertargetingrecordthanmostofthepublicprogramsandmatchthetargetingresultsofprogramsadministeredbyFONCODESandPRONAA(Graph20).

48FiszbeinandLowden(1998)havecollectedalargenumberofexamplesofhowgovernment,businessandcivicpartnershipshaveworkedsuccessfullyforpovertyreductioninLatinAmerica.

Page47

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Moncada,Gilberto(1996),PerfildelaPobrezaenPeru,1994,inWebb,RichardandGilbertoMoncada,ComoEstamos?,InstitutoCuánto,Lima,pp.97135.

Moser,Caroline(1996),UrbanPoverty:HowdoHouseholdsAdjust?,in:EcuadorPovertyReport,WorldBank.

OxfordAnalytica(1998),Peru:PovertyPrograms,TheFujimoriGovernment'sStrategytoTackleRuralPoverty,July30.

Persaud,Thakoor(1992),HousingDeliverySystemsandtheUrbanPoor,AComparisonAmongSixLatinCountries,LatinAmericaandtheCaribbeanRegionalStudiesProgram23,WashingtonD.C.

Ravallion,Martin(1994),PovertyComparisons,HarwoodAcademicPublishers,Chur.

Rodriguez,Edgard(1998),TowardaMoreEqualIncomeDistribution?TheCaseofPeru199497,backgroundreportforthisstudy,processed,PovertyReductionandEconomicManagementNetwork,PovertyGroup,WorldBank.

Rodriguez,JoséandDavidAbler(1998),AsistenciaalaEscuelayParticipacíonenelMercadoLaboraldelosMenoresenelPeruentre1985y1994,processed,PennsylvaniaStateUniversity.

Saavedra,Jaime(1998),WhatDoWeKnowAboutPovertyandIncomeDistributioninPeruwithEmphasisonItsLinkswith

EducationandtheLaborMarket,backgroundreportforthisstudy,GrupodeAnálisisparaelDesarrollo,Lima.

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Saavedra,JaimeandAlbertoChong(1999),StructuralReform,Institutions,andEarnings:EvidencefromtheFormalandInformalSectorsinUrbanPeru,JournalofDevelopmentStudies,forthcoming.

Saavedra,JaimeandJuanJoseDiaz(1997),ElRoldelCapitalHumanoenlaDistribuciondelIngreso,mimeo,GrupodeAnálisisparaelDesarrollo,Lima.

Saavedra,Jaime,R.MelziandA.Miranda(1997),FinanciamientodelaEducation,DocumentodeTrabajo24,GrupodeAnálisisparaelDesarrollo,Lima.

Schady,Norbert(1998),PickingthePoor:IndicatorsofGeographicalTargetinginPeru,WoodrowWilsonSchoolofGovernment,PrincetonUniversity,processed,Princeton.

UnitedNations(1997a),HumanDevelopmentReport,NewYork.

UnitedNations(1997b),InformeSobreelDesarrolloHumanodelPeru,Lima.

White,MichaelJ.,LorenzoMorenoandShenyangGua(1995),TheInterrelationofFertilityandGeographicMobilityinPeru:aHazardsModelAnalysis,InternationalMigrationReview29,pp.492514.

WorldBank(1996),DidtheMinistryofthePresidencyReachthePoorin1995?,processed,CountryDepartment6,LatinAmericaandtheCaribbeanRegion,WorldBank.

WorldBank(1998),WorldDevelopmentIndicators,WashingtonD.C.

Yamada,Gustavo(1996),UrbanInformalEmploymentandSelf-EmploymentinDevelopingCountries:TheoryandEvidence,EconomicDevelopmentandCulturalChange44,289314.

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AnnexI:PanelStudyofHouseholdsThisannexbrieflyrecapstheresultsofstudyingthepanelsubsampleoftheLivingStandardMeasurementSurveysforwhichthesamehouseholdswereinterviewedin1994andagainin1997.

Ourbasicmodelconsistedofexpressingthegrowthofpercapitahouseholdexpendituresfrom1994to1997asafunctionofalargenumberofexogenousvariables,suchasaccesstobasicservices,initialeducationandconsumptionlevel,etc.Manyofthesevariablesarehouseholdcharacteristicsintheinitialyear(1994).Theyincludeyearsofthehouseholdhead,educationofthehouseholdhead,migration,languagespokenetc.

Sincemanyofthehouseholdschangedinsizeorheadshipoverthethreeyears,welookedatthreedifferent,increasinglyrestrictivepanelsubsamplestotesttherobustnessoftheestimates.Thefirstsampleincludesthetotalpanelof891households(fullsample).Thesecondsampleincludedonlythosehouseholdsthathadthesameheadshipin1994and1997(690households).Thethirdandmostrestrictivesampleincludedonlythosehouseholdsthatneitherchangedinheadshipnorcompositionovertheyears-forthissubsample,percapitagrowthinhouseholdconsumptionisnotinfluencedbyadditionsorattritionfromthehousehold.

OurfirstresultconfirmsotherpanelanalysesinPeru:mobilityinthesampleisveryhigh,i.e.alargepercentageofhouseholdschangedtheirrelativepositionbymorethanonewelfaredecileoverthethreeyears(seeGlewweandHall1995,Escobaletal1998).Inabsoluteterms,about55percentofallhouseholdsrecordedapercapitaconsumptiongrowthofmorethan10percent,about15percent

recordedmoreorlessthesameconsumptionleveland30percenthadaconsumptionpercapitalevelin1997morethan10percentbelowtheirlevelin1994.49

Regressionsresultsusingthethreesamplesaresimilar.TheregressionresultforthefullpanelisreproducedintableA1.1.Robustresultsfromtheregressions,whichholdforavarietyofdifferentspecificationsandapplicationtothedifferentsubsamples,are:

a.Female-headedhouseholds.Controllingforallotherinfluences(education,initialconsumption,householdsize,dependencyratioetc.)female-headedhouseholdsfaredbetterthanmaleones,increasingpercapitaconsumptiongrowthby0.11percent(inthefullpanel).

b.Migrantfamilies.Wedonotfindevidencethatmigranthouseholds(i.e.,thehouseholdheadwasborninadifferentlocationthanhe/shelivedin1994)faredworsethannonmigrantfamilies.Theparameterispositiveandinsignificantinthefullsampleandbecomesmarginallysignificantandpositiveinthemostrestrictedsample.

49Inpart,thehighmobilitycouldbeduetomeasurementerrors.Thiscancauseseriouseconometricproblemsfordifferenceorgrowthregressions(seeDeaton1997,pp.108110).

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c.Nativelanguage-speakers.Language,andwithitindigeneity,mattersalot.Evenwhenwecontrolforothervariablesthatarecorrelatedwithlanguagesuchasgeographiclocation,nativelanguage-speakinghouseholdsstillfellbehindSpanish-speakinghouseholds(-0.10percentinthefullsample).

d.Basicinfrastructure.Wefindevidenceofincreasingreturnstothenumberofserviceshouseholdscommand.Thisresultsstandsinallthreeiterationsoftheregression.Inthefullsample,holdingallotherinfluencesconstant,ifahouseholdhadaccesstooneoffourservices(telephone,electricity,water,sanitation)in1994,thisincreasedthepercapitagrowthrateby0.04percent(insignificant).Ifthehouseholdhadaccesstotwoservices,percapitagrowthwas,onaverage,0.05percenthigher(themarginalreturnonthesecondserviceis0.01percent).However,marginalreturnsincrease:thethirdservicehasamarginalreturnof0.11percentandthefourthserviceof0.12percent.Electricityisthemostimportantservicelinkedtohouseholdwelfareimprovementsinruralareasandatelephoneinurbanareas.

e.Householdsize.Householdsizeinfluenceswelfaredevelopments.Resultsfromregressionsofthefullsampleaswellastherestrictedsamplessuggestthat(i)largerhouseholdsfareworsethansmallerones;and(ii)thisrelationshipisnotlinear;thelargerthehousehold,thelowertheadditionalreductioninwelfare.Additionally,wefindthatthedependencyratio(numbernon-incomeearnerstoincomeearners)hasamarginallysignificantindependentnegativeinfluenceonhouseholdpercapitaconsumptiongrowth(inmostrestrictedsampleonly).Therelationshipbetweenhouseholdsizeandwelfaredevelopmentsrequiresfurtherstudysinceitisnotapparentwhylargerhouseholds(independentfromthedependencyratio)shouldhavelowerwelfareincreasesthansmallerhouseholds.

f.Educationandexperience.Thehighertheeducation(andthemore

workexperience)ofthehouseholdheadin1994,thelargerthegrowthinpercapitaexpenditures.ThismirrorsthecommonobservationinPeruthatthebettereducatedandmoreexperiencedhaveprogressedrelativelymorethanthelesseducatedinrecentyears.Onemoreyearofeducationincreasedthehouseholdpercapitaconsumptiongrowthrateby0.03percent.

g.Financialsavings.Householdsthatcommandedfinancialsavingsinboth1994and1997achievedhigherwelfaregrowthrates(0.20percent).

h.Householdswithhome-basedbusinesses.Bothurbanandruralhouseholdsthatstatedthattheyusedatleastoneroomintheirhouseforbusinesspurposeswerebetteroffthanhouseholdsthatdidnothavethispossibility.Thesehouseholdsoftenhadinformalearningpossibilities.Thisresultholdswhencontrollingforallotherfactorsthatinfluenceconsumptiongrowth.

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TableA1.1:PanelGrowthRegressionSource SS df MS Numberof

obs=891

F(15,875)= 34.07Model109.423594 157.29490627 Prob>F= 0.0000

Residual109.423594875.214145428 R-squared= 0.3687AdjR-squared=

0.3579

Total296.800843890.333484094 RootMSE= .4627619794c Coef. Std.Err. t p>|t

|[95%Conf.Interval]t

lgpcr94b -.6895338 .031891 -21.6220.000 -.7521257 -.626942yrsh .0311574 .0043992 7.0830.000 .0225232 .0397915

quechua -.0951024 .0402248 -2.3640.018 -.1740507 -.0161541edadh .0058017 .0012675 4.5770.000 .003314 .0082893female .108005 .0449603 2.4020.017 .0197625 .1962475famtam -.1021141 .027817 -3.6710.000 -.1567099 -.0475183famtam2 .0048443 .0020883 2.3200.021 .0007457 .008943econroom .1494465 .0403158 3.7070.000 .0703196 .2285734ahfin4y7 .2040275 .090935 2.2440.025 .0255512 .3825037migroh .0457797 .0321832 1.4220.155 -.0173855 .108945drt94 -.0091593 .009849 -0.9300.353 -.0284898 .0101712

s1 .0417148 .0527044 0.7910.429 -.061727 .1451566s2 .0541988 0558559 0.9700.332 -.0554285 .163826s3 .163079 .0498228 3.2730.001 .0652929 .2608651s4 .2769414 .0695599 3.9810.000 .1404177 .4134651

_cons 5.117684 .2790731 18.3380.000 4.569953 5.665414VariableNames:'lgpcr94b'logofconsumptionpercapitain1994;'yrsh':yearsofeducationofthehouseholdheadin1994;'quechua':householdheadreportsquechuaasmothertonguein1994;'edadho':ageofthehouseholdhead1994;'female;':dummyvariableforheadshipofhouseholdbeing1iffemalehouseholdheadin1994;famtam;householdsize1994;famtam2:householdsizesquared1994;'econroom':dummyvariablebeing1forhouseholdsthatusedatleastoneroomintheirhouseforbusinesspurposesin1994;'ahfin4y7'dummyvariablebeing1forhouseholdsthathadfinancialsavingsinboth1994and1997;'migroh':

dummyvariableformigrantsbeing1ifthehouseholdheadwasnotborninthesamelocationthanhe/shelivedin1994;'drt94':dependencyratioin1994definedasratioofincomeearnerstonon-incomeearners;'s1':dummyvariableforhouseholdsthathadoneservice(water,electricity,sanitation,telephone)in1994;'s2':dummyvariableforhouseholdsthathadtwoservicesin1994;'s3':dummyvariableforhouseholdsthathadthreeservicesin1994;'s4':dummyvariableforhouseholdsthathadfourservicesin1994;_cons:constantterm.

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AnnexII:Methodology

Introduction

Peruisoneofthecountriesthatpioneeredcomprehensivehouseholdsurveysaimedatmeasuringpovertyandwell-being.ThefirstLivingStandardMeasurementSurvey(LSMS)inPeruwasconductedin1985bytheNationalStatisticalInstitute(INEI)andsincethentheInstitutoCuántohasconductedahostofothersurveys.Whileeachsurveyaddedormodifiedseveralquestions,partlybecauseofthespecificinterestoffundingorganizations,thecoreofthesurveys,withtheirfocusonhousingconditions,education,health,migration,thelabormarket,andagriculturalactivity,hasstayedremarkablyconstant.ThetwomostrecentandlargestCuántosurveysarethoseusedinthisstudy:the1994and1997EncuestasdeNivelesdeVida(ENNIV).Theyemployedasampleframetoachieverepresentabilityintheurbanandruralareasofthethreeagro-climaticzonesinthecountry(Coast,Sierra,Selva)plusLima.

Workingwithhouseholdsurveydatarequiresmany-oftencumbersome-stepsofdatacleaningandconsistencychecksbeforetheactualempiricalinvestigationscanbegin.Especiallywhencomparingdifferentvariablesovertime,oneofourprimaryaims,cautionisnecessary.Andthisstatementholdsevenmorewhentheaimistocompareanartificiallycreatedvariablebetweensurveys.Forpovertyanalysisthisvariableiscentralaswefirsthavetoderiveamonetarywelfaremeasure(consumptionorincome).Further,themonetaryaggregateneedtobedeflatedoverbothtimeandspace.Andthenthe(in)famouspovertylinesneedtobederivedbeforethesimplestofallcomparisons-calculatingheadcountrates-cantakeplace.Alongthe

way,manyassumptionshavetobemade.

ThisannexcontainsadescriptionofhowweusedthetwoLSMSsurveysfromtheInstitutoCuánto.Westartwithashortbackgroundsectiononpovertycomparisonsingeneral,whichstressestheimportanceofdefiningwelfareinaconsistentmannerwhenconductingcomparisonsovertime.Wethendescribehowweaggregatedconsumptionexpenditures,payingparticularattentiontotheircomparabilitybetweenthetwosurveyyears.Incomedefinitionsarealsoincluded.Wenextexplainhowwederivedpovertylinesfor1994and1997andthenecessarypriceadjustments.Finally,wereporttheresultsofseveralsensitivityanalyseswithrespecttoadultequivalenceandeconomiesofscale.

Background:PovertyComparisonsinTime

Oneofouraimswhenanalyzingthe1994and1997LivingStandardMeasurementSurveyswastocomparepovertyandwelfarechangesofthePeruvianpopulationovertime.Atfacevaluethisdoesnotseemtobeverydifficult.Bothsurveysincludehouseholdincomeandconsumptionthatcanbeconvertedintopercapitatermsandthencomparedtocertainabsolutestandards,thepovertylines.Headcountrates,povertygaps,andpovertyseveritycanbecalculatedandcomparedinreferencetothesepovertylinesovertime.

Butforanumberofreasons,povertycomparisonsusingconsecutivesurveysaregenerallyquitecumbersomeanddifficult.Firstofall,ithastobeensuredthatthesamplingframe(fromwhichfactorexpansionsarecomputed)isthesameforthetwoyearsandthatthedefinitionswhichdeterminethesamplingprocessareidentical.Forexample,ifstratification

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ofthesampleisconductedwithrespecttourbanandruralareas,thelatterneedstobedefinedinthesamewayinconsecutiveyears.Thesameholdsforotherstratifiedvariables,betheyofapoliticalorsocio-economicnature.Forexample,inadditiontothenationallyrepresentativehouseholdsurveysmentionedabove,Cuántoalsofieldedonerelativelysmallsurveyin1996.Thiswasapurepanelsurvey,asall1,491householdsinterviewedwerealsopartofthelarger1994survey.Whilestatementscanbemadeaboutthecomparisonofpovertybetween1994and1996forthepanelhouseholds,50generalizationsforthewholecountrycannotbemade.Eveniftheselectionofthepanelhadbeencompletelyrandom(i.e.,allhouseholdsformingpartofthe1994surveyhadthesamechanceofbeingselectedforthepanel),the1996surveywouldnothavebeennationallyrepresentative.Newlyformedhouseholdsafter1994hadazeroprobabilityofbeingselectedinthe1996survey.Althoughthebiasbetweentwoyearsmightbesmall,itseffectcannotbequantified.

Second,povertycomparisonsarebasedonanumberofverystringentassumptions.Themostcommonmethodofconductingpovertycomparisonsistobaseallnominalincomeandconsumptiondatafromdifferentsurveysononetimeperiodandoneregion;i.e.,todeflatenominalvariablesinspaceandtimeandhenceconvertthemintorealvalues.51Theserealvaluesarethencomparedtoaconstantpovertylinerepresentingaminimumconsumptionbasket.Generally,thebasketitself(atleastthefoodbasket)isderivedfromactualconsumptionpatternsofthepoorsothatitisappropriateforthetypeofanalysisbeingcarriedout.Thisbasketofgoodsissupposedtopresentacertainwelfarelevelthatcanbecomparedacrosshouseholds.Oneoftheimportantassumptionsunderlyingsuchwelfarecomparisonsisthathouseholdshavethesametastes;i.e.,thatthewelfarehouseholdsderivefromconsumingthebasicbundleofcommoditiesisidentical.Althoughthisisanidealization,wecan

neverthelessthinkofthebasicbundleofgoodsasayardstickagainstwhichwemeasurepeople's(relative)welfare-weexpressthe(relative)welfareofhouseholdsashowmanytimescantheyconsumeagivenbundleofgoods.

Welfarecomparisonsovertimeleave,ifatallpossible,thisyardstick(orbasicbasketofgoods)constant.Hence,thecompositionofthefoodbasketwithallitscomponentsoffruits,vegetables,meats,etc.,iskeptconstant,asisthenon-foodcomponentssuchashousing,clothing,services,theuseofdurableitems,andthelike.However,astheassumptionofidenticaltasteswasashortcut,soisthis.Overtime,relativepricesamonggoodschange.Householdsadjusttotheserelativepricechangesbychoosingadifferentmixofcommodities,generallyincreasingtheconsumptionofrelativelycheaperproductsandreducingintakeofrelativelymoreexpensiveones.Abasketofgoodsthatwasrepresentativeofthepoor'sconsumptionpatterninabaseperiodhenceisnotnecessarilyrepresentativeoftheconsumptionpatterninadifferenttimeperiod.Bothrelativepricechangesandmodificationsinpreferencescanaccountforsuchshiftingconsumptionpatterns.Welfarecomparisonsusingafixedbasketintimehenceare-again-onlyapproximations.52

50InstitutoCuánto(1997)producedastudycomparingpovertyinthe19941996panelandwascarefulnottogeneralizeresultstothewholeofPeru.51See,forexample,FerreiraandLitchfield(1998)52Thisstudyusesafixedbasketoftotalgoods(foodandnon-foodgoodsalike)toderivepovertylinesandconductpovertycomparisons.ThisdiffersmarkedlyfromthetraditionalpovertyanalysisinPeru,whichkeepsonlythefoodbasketconstantovertimeandderivedthenon-foodcomponentendogenously.

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Third,asmentionedabove,carefulpricedeflationiscrucial.Anumberofdifferentmethodshavebeenusedinpaststudiestoderivespatialandtimeindicesinordertomakeconsumptionexpenditurescomparableamonghouseholdsindifferentlocationsandofdifferentsurveyyears.Butallofthemrequiretheavailabilityofregionallydistinctpriceindicesforbroadproductgroups.Inmanycountriessuchinformationdoesnotexist.InPeru,however,detailedpriceinformationexistsforfoodproductsinallregionsandfornon-foodcategoriesin25urbancenters.Aswillbeshown,wecanusethisinformationtoadjustnominalconsumptioninallsurveyyears.

Fourth,ifthebasketofgoodsiskeptconstantovertime,thedefinitionofconsumptionneedstobethesameaswell.Povertymeasurementcanbeseriouslydistortedifthedefinitionofconsumptionchangesovertime.Forexample,consecutivesurveysmightaddaquestiononexpendituresandauto-consumptionofaveryspecificfooditemthatwasnotaskedforbefore.Obviously,evenifthetruefoodconsumptionofhouseholdsiscompletelyidenticalinthetwosurveyyears,itwouldappearonpapertobehigherintheyearinwhichtheadditionalquestionwasasked.Ifthebasketofgoodsagainstwhichwecompareconsumptionexpendituresofhouseholdsisfixed,however,addingfurtherconsumptionitemswillleadtoanunequivocalreductioninpoverty.53

Cautionalsoneedstobetakenifthemeaningorphrasingofquestionsintheconsumptionmodulechangesovertime.Evenifitemsforwhichhouseholdsareaskedtoreportexpendituresorauto-consumptionareidentical,thephrasingofquestionscanhaveaprofoundimpactonthelevelandstructureofresponses.AnexamplefromtheCuántosurveys1994and1997isusedbelowtoillustratethispoint.

Finally,povertycomparisonsshouldideallyestablishwhetherornot

observedtrendsinstatisticsarerobust.Thiswouldimplyvaryingsomeoftheunderlyingproceduresforconsumptionaggregation,suchasimputationproceduresortestingtheeffectofimplicitassumptionsabouteconomiesofscaleoradultequivalencescales.Further,thepovertylinecanalsobevariedoverawiderangeofdifferentvaluestotestwhetherthechoiceofpovertylinemattersforthedirectionofwelfarechanges.

53LanjouwandLanjouw(1997)showthatifconsumptionquestionschangeovertimesothatthedefinitionsimplycannotbeheldconstant,asecondpossibilityistokeeponlythefoodbasketconstantandderivethenon-foodbasketimplicitlybycalculatingtheEngelcoefficient.Theyshowthatthiswillgiveconsistentestimatesofpovertyunderanumberofassumptions,includingahomogenousrelationshipbetweenfoodexpendituresandtotalexpenditures.Further,betweenthesurveyyearslittleornorelativepricechangesbetweenfoodandnon-foodgoodsshouldoccur.

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DefiningWelfare

Consumption

Theconsumptionaggregateweareusingisdesignedtobecomparableforthe1994and1997surveyyears.Althoughthesurveysshowaveryhighdegreeofhomogeneity,thequestionnairedidchangeinseveralways:newproductswereadded,productgroupswerechanged,separateproductsinoneyearweresummedupinthenextyear,andquestionswerereformulatedwhichgavethemadifferentmeaning.

Wealsomademanysmalladjustmentsinalmostallcomponentsoftheconsumptionaggregate.Table1containsthedescriptionfordifferentproductcategoriesandtheconsumptiondefinitionweused(computerprogramsareavailableonrequest).54Ascanbeseen,certainexclusionsandinclusionsofsub-componentsweremadeintheeducation,health,semi-durable,transferandauto-consumptionsections(fromownbusiness).Wecouldnotincludethedepreciationstreamfromdurableconsumergoodsbecausethe1994surveydidnotincludetheagestructureofthehouseholddurableconsumergoods,whichmeantthatdepreciationratescouldnotbecalculated.55Similarly,furniturepurchaseswerenotincluded.Thefood,rentandsocialprogrammodulesrequiremoreelaborateexplanation.

FoodModule.Whilethefoodmoduleofthequestionnaireappearstobealmostcompletelyidenticalin1994and1997,Cuántointroducedoneconsiderablemodification.Specifically,Cuántoaddedonesupplementaryquestiontothefoodmodulein1997whichreadstotalautoconsumoyautosuministro.Theconsequenceofincludingthiswell-intentionedquestionwasthatmorethanonethirdofallsamplehouseholdsandtheirinterviewers(closeto1,300)chosetorespondonlytotheaggregatequestion-therebyavoidingdetailedanswers.Generally,ithasbeenshownthatdetailedconsumptionquestions

haveaclearadvantageoveraggregatequestionsastheyhelprespondentstorecollectquantitiesandexpendituresbetter.Lanjouw(1997)reportsthatunder-declarationcanbesignificantinshorterquestionnaires,especiallyforlower-incomegroups.

54SendemailtoJhentschel@worldbank.org.55The1997surveyincludesthisagestructure.Currentconsumptionfromthestockofdurablegoodscanthenbeestimated(themedianagecanbecalculatedforeachtypeofgoodassumingthatthedepreciationrateishalfthelifedurationoftheproducts).Giventheageofindividualproductsperhousehold,onecouldindividuallycomputetheexpectedremaininglifeofeachproduct.

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TableA2.1.:DefinitionoftheConsumptionAggregate,1994and1997Item 1997 1994Consumerdurables

Excluded excluded

Dailynon-food,Other

allpurchaseandautoconsumptionincluded(Z3A,Z3B)exceptforexpendituresonpublictelephones,asnotin1994(z2=109)

allpurchasesandautoconsumption

In-kindconsumptionfromfirm/business

Includesautoconsumptionfromfirms(W19)

Included

In-kindconsumptionfromwork

Primaryandsecondaryworkoverlast7days,primaryandsecondaryworkoverlast12months(adjustedfortimeperiodworked)(M11B,M12B,O11B,O12B,R12B,R13B,T12B,T13B)

includedasin1997(identicalquestions)

Education directexpendituresineducationsectionincluded(F10A,F10B,F10C,F10D,F10E)

schooluniformsexcluded(asincludedintheservicessections).Also,1997questionnaireaskedforfrequenciesbut1994surveydidnot.Hence,weusedmedianfrequenciesfromthe1997surveyforevaluatingpaymentofmatriculation,books,transportin1994.Also,aseparatequestionsonexpenditureforchildrenunderage6in1994surveysexcludedbecausenotin1997survey.

Furniture Excluded(anddepreciationratecannotbecalculated)

Excluded

FoodmodulePurchasesandvaluedautoconsumption(AE4,AE5,AE6andAE7)

purchasesandvaluedautoconsumption(identicalapartfromminorandnegligibledifferentgrouping);however,anadditional

included questionwhichallowedhouseholdstoonlygiveoneaggregatefigurefortotalfoodpurchasesdidcausecomparabilityproblems(seetext).

Healthexpenditure

directhealthexpenditureinhealthsectionincluded(H11A,H11B,H15,H19);butexcludedinservicessection(AA1=125,126,127)asrecallperioddifferentandnotcleariftheseareadditionalorthesameproductsmentionedinthehealthsection

sameas1997:expendituresinhealthsectionincluded,inservicesectionexcluded.However,examiningtheshareofhealthexpenditureintotalexpenditure,wefoundanumber(61)ofoutlierhouseholdswhichstatedthattheyspentmoreof50percentoftheirtotalexpenditureonhealth.Thisdidnothappenin1997.Hence,weexcludedtheseoutliers.

Houseexpenditures

water(D9A),light(D12A),heatingandcookingfuel(D14A),telephone(D18BandD20A),municipalfees(D22A)[note:municipalarbitrationexcluded]

allincluded

Paymentsforhouse(repaymentofcredit)

Excluded Excluded

Rent Excluded(questionsdifferent).Seeexplanationintext.

excluded(questionsdifferent).Seeexplanationintext.

Semi-durablesandservices

onlypurchaseincludedasthe1994questionnairedidnotincludeautoconsumption

onlypurchaseincluded;

Socialprograms

onlyfoodaidincludedas1994surveydidnotaskforothersocialprogramtransfers;excludes'alimentoportrabajo'ah1=506asnotin1994survey

foodaidincluded(ascapturedinthefoodsectionunderaj02=327andak02=327);excludesa101=09asCuántomaintainsthatquestiona101=09wasimputedintoaj03=327

Transfer Ceremonies(AD1-02), ceremonies(in1994inservicesmodule),

Transferexpenditures

Ceremonies(AD1-02),directtaxes(AD1=03),socialsecurity(AD1=04),membershipfees(AD1=07),donations(AD1=09).Insurancequestionsexcludedasnotin1994survey(AD1=06).

ceremonies(in1994inservicesmodule),socialsecurity,membershipfees,donations,directtaxes

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TableA2.2:DetailedandAggregateFoodModuleResponses

quintile foodshareofhouseholdsanswering

detailedquestions

foodshareofhouseholdsanswering

aggregatequestion1 67.9 68.12 60.3 60.23 56.2 53.44 49.7 47.95 43.9 39.2Source:ENNIV(1997),owncalculations.Populationquintilesdefinedbytotalrealexpenditures.

Whilewedofindapatterninresponseswhencomparingthefoodshareofhouseholdsansweringthedetailedquestionnairewiththefoodshareofhouseholdsthatonlygiveoneaggregatefoodexpenditurevalue,wehaveoptednottoadjustthisvariable.TableA2.2showsthatthefoodshareofhouseholdsansweringthedetailedquestionstendstobesignificantlyhigherthanthefoodshareofhouseholdsgivingonlyone,aggregateestimatefortherichestthreequintiles.Weopted,however,nottomakeadjustmentsfortworeasons:(a)inthelowesttwoquintiles(whichareourprimaryconcerninapovertystudy),themeandifferenceisnotverylarge;and(b)itisextremelydifficulttomakeanadjustmentasthepercentageoftotalexpenditurespentonfoodshowsenormousfluctuationsacrosshouseholdsinonequintile(thisisgenerallyobservedinhouseholdsurveys,seeLanjouwandLanjouw1997).Itisthereforequestionabletofixthefoodshare,whichaccountsforthebulkofexpenditures,toanaveragenumberacrosshouseholds.

Rent.Nexttofood,theactual(orimputed)rentalvalueofthehouse

tendstobethemostimportantbudgetitemforthepoorandnon-pooralike.Wethereforewereveryeagertoincludethisvariableinourconsumptionaggregate,asitaddsanimportantwelfarecomponentoffamilies:howmuchspacehouseholdshave,whetherthehouseismadeofweather-resistantmaterial,howclosetheshelterisfromthenearestmarket,whattransportationpossibilitiesexist.Allsuchfactorsenterintothedeterminantsofthehousingvalue,whichwewereeagertoincorporate,albeitensuringthatwehaveconsistencyovertheyears.

Boththe1994and1997surveyscollectedinformationon(a)actualrentpaid;and(b)self-estimatedimputedrentfromthehouseholdsthatwereowner-occupiers.Twoproblemsarosehere.First,wehadtoundertakesomesimpleimputationsofthevalueofhousing.Thesehadtobecarriedoutforthosehouseholdsthatprovidedneitheractualnorestimatedrentalvalueoftheirhousing.Forthispurpose,weusedsimplehedonicregressionsinwhichwepostulatedthevalueofhousingtobeafunctionofthestockofassetsofthehousehold,regionaldummies(capturingpricevariations),andbothhousing(material,size)andhousehold(size)characteristics.Basedontheirhousing,household,andassetcharacteristics,wepredictedhousingexpendituresforthosehouseholdsthatdidnotreportavaluefortheactualorestimatedrentalvalueoftheirhouse-238householdsin1994and13in1997.

Thesecondproblemthatarosewasmuchmoresevere.Thequestionnairehadchangedbetweenthetwosurveyyearssoweneededtotestwhetherwecouldindeedincluderentalvaluesofthehousewithoutcompromisingthecomparabilitybetweenthesurveys.Whilebothsurveyshadaquestionrecordingtheactualrentpaidbyhouseholds,the1994surveyhadafollow-upquestionforowner-occupiersinwhichhouseholdswereaskedhowmuchtheywouldchargeiftheyweretorenttheirhouse.Incontrast,the1997questionnairequeriedowner-occupiershowmuchtheywouldbe

willingtopayhadtheytorenttheirown

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house.Ourinitialhypothesiswasthatthechangeinthequestionwouldhaveonlyamarginalimpactonthestructureandlevelofthisvariable.

Weconductedseveralteststoexplorewhethertherentsectionswerecomparable.Thefirstoneinvolvedtheimputationregressionsreportedabove.AsLanjouwetal(1996)haveshown,suchimputationregressionscanbeusedtopredicthousingpricesindifferentregionsofthecountrywhilecontrollingforthequalityandcharacteristicsofhousing.Theideaissimple:usingthemedianvaluesforallexogenousvariables(assetvariables,housingandhouseholdcharacteristics,geographicdummyvariables)andtheestimatedparametervalues,wederivedtheexpectedpriceofastandardhouseinallregionsfor1994.Usingthesamemedianvaluesoftheexogenousvariables(aswewanttocontrolforqualityovertime)butnowemployingparameterestimatesfor1997,wecouldcalculaterentalvaluesfor1997aswell(asthisiswhenthechangeinthequestionnairetookplace).Whilethechangeinthehousingpriceitselfisinteresting,wecannowalsoaddonemorecontrolvariable,asINEI,thePeruvianStatisticalInstitute,compilesavalueforhousing(alquiler)for25citiesinthecountry.TableA2.3showstheresultsforthechangebetweenJune1994andOctober1997(themonthsofthesurveys).AccordingtotheregionalINEIpricedata,allurbanregionsexperiencedconsiderablyslowerrentinflationthan(implicitly)recordedinthesurveys.

TableA2.3:RentalValuesin1994and1997Area PredictedRental

Value,1994(solesperyear)

PredictedRentalValue,1997

(solesperyear)

ChangeinPredicted

Value,1994/97(%)

ChangeinRentalIndex,INEI(%)

Lima 1701 2593 52.4 34.2Coast 1184 1822 53.9 35.5

UrbanCoastRural

221 445 101.4 -

SierraUrban

731 1452 98.6 35.9

SierraRural

144 537 272.9 -

SelvaUrban

764 1371 79.5 26.7

SelvaRural

200 372 86.0 -

Source:StaffestimatesbasedonENNIV1994and1997;INEIRegionalOffices.

Thesecondpossibilitytotestthechangeintherentalvariableovertimewastolookathowthesamehouseholdsevaluatedtheirrentalvaluein1994and1997.Inlinewithitstradition,Cuántoincludedinits1997sampleabout900householdsthathadalreadybeeninterviewedin1994.Wedividedthispaneldatasetinto10rentdeciles;i.e.,thehouseholdsreportingthelowestrentalvaluesweregroupedindecile1,thehouseholdswiththehighestindecile10.Usingatransitionmatrix,wecouldthenseehowthisrankingofhouseholdswithrespecttotherentvariablechanges.Sincethehouseholdsliveinthesamedwellingforbothsurveyyears,wewouldassumethattherankingofhouseholdsstaysverystableifthedifferentquestiondoesnothaveanimpactontheirreportingpatterns.However,wefindthatrankings

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changedconsiderably:onlyabout25percentofthepanelsamplewerelocatedonthediagonalinthetransitionmatrix,whichimpliesthattheydidnotchangetheirdecilerankingbetween1994and1997.Anadditional25percentwereoffbyonedecilebutroughlyhalfofthetotalsampleshowedchangesofatleasttwodecilerankings,whichimpliessignificantrankingchanges-althoughtheseareidenticalhouseholdslivinginthesamedwellingsin1994and1997.

Finally,welookedattheoverallexpenditurecomposition.Ourhypothesiswasthatthechangeinthequestionnairewouldlikelyleadtoalowershareinhouseholds'subjectiveevaluationoftheirrentalvaluein1997comparedto1994(sincein1997householdswereaskedwhattheywouldpayfortheirownhouseinrent).Butthisdidnotprovetobethecase-actually,theshareoftotalexpenditureon(actualandself-declared)rentincreasedmarginallyoverthe19941997period(from14to16percent).However,thisaveragedoesmarkquitelargevariationsinrentalvaluebetweentheyears:actualandimputedrentwasavariablewithaveryhighfluctuationasashareoftotalexpenditures-rentpatternsalmostreversedincertainregions.TableA2.4tabulatesthechangingfood-andrentshareoftotalexpendituresbetween1994and1997.TableA2.4alsoshowsthatthevariationinthefoodsharebetween1994and1997issignificantlyreducedifrentisexcludedasacomponentoftotalconsumption.

Giventhesefindings,weconcludedthatchangingthequestionregardingtherentvariablehadasignificantimpactonresponsesand,especially,theirstructureindifferentexpendituregroups.Sinceoneofourmainaimswaswelfarecomparison,wethereforechosetoexcludetherentalvaluefromtheconsumptionaggregation.Theincomedefinitionalsodidnotincludetherentalvalue.

FoodDonations.Thequestionnairealsochangedconsiderablybetween1994and1997withrespecttohowfooddonationsare

treated.In1994,thesewerenotexplicitlyaskedforbutincorporatedintotwodifferentquestions.First,inthesectiononfoodconsumption,householdsenteredthevalueofpreparedfoodproducts.56Second,householdswereaskedhowmuchincomeorvalueinproductstheyreceivedfromnon-profitorganizations(examplesgiveninthequestionnairewereVasodeLeche,ClubdeMadreandCARITAS).57Cuántoholdsthatthevalueoffooddonationswasactuallyincludedinthepreparedfoodquestioninthefoodmodulewhentheoriginaldatawereprocessed.Thequestionnairewasconsiderablydifferentin1997.Cuántoaddedanentiresectiononaccesstosocialservicesinwhichhouseholdsreportedthevalueoffoodreceivedbyprogramandfundingsource.Inaddition,thefoodmodulecontinuedtoincludethesamequestionthathadbeenaskedin1994;i.e.,thevalueofpreparedfoodproductsconsumedbythehousehold.

56Thisisinthefoodmodulesectionin1994,variablesaj02andak02(rubrique327).57Thisreferstocodeal01=09inthe1994questionnaire.

TableA2.4:ExpenditurePatternsandConsumptionDefinitionIncludingImputedRent ExcludingImputedRent

Area QuintileFoodshareFoodshared(Foodshare)d(Rentshare)FoodshareFoodshare1994 1997 1994/1997 1994/97 1994 1997

Lima 156.84 50.13 -6.71 1.64 66.6 59.95252.75 48.29 -4.46 -0.30 63.36 57.8350.27 47.2 -3.07 -0.77 61.68 57.38445.99 41.08 -4.91 -0.44 58.31 51.44534.21 33.18 -1.03 -5.91 49.2 43.81

Coast 156.95 49.45 -7.50 8.09 64.98 62.78Urban 252.86 47.93 -4.93 4.13 61.89 59.09

350.55 48.7 -1.85 1.51 60.75 59.37447.82 44.9 -2.92 0.85 57.87 54.89539.22 42.11 2.89 -2.03 49.77 52.39

Coast 171.88 69.2 -2.68 -0.02 78.66 75.78Rural 268.52 68.39 -0.13 -0.87 74.39 73.51

368.24 67.28 -0.96 0.58 73.46 72.72459.76 63.98 4.22 -0.47 64.85 69.05557.42 58.82 1.40 -1.30 63.49 63.98

Sierra 158.91 48.9 -10.01 4.84 66.93 59Urban 256.64 47.13 -9.51 4.23 63.82 56.04

348.3 46.49 -1.81 1.39 56.68 55.81448 42.92 -5.08 2.28 57.52 52.79541.89 40.76 -1.13 -1.15 52.65 50.65

Sierra 172 69.28 -2.72 2.45 78.69 78.17Rural 271.43 64.93 -6.50 6.40 76.45 74.64

369.43 64.93 -4.50 3.90 75.12 73.33469.87 63.95 -5.92 3.85 74.3 70.9562.98 63.4 0.42 0.13 69.44 69.73

Selva 163.02 52.59 -10.43 11.27 70.06 66.74Urban 261.65 55.57 -6.08 6.71 69.6 68.02

356.39 52.68 -3.71 4.11 63.59 62.59453.08 50.46 -2.62 0.70 62.56 60.23546.48 47.33 0.85 -1.43 56.07 56.35

Selva 172.76 68.66 -4.10 0.32 81.08 76.74Rural 273.56 68.24 -5.32 1.50 78.98 74.56

Rural 273.56 68.24 -5.32 1.50 78.98 74.56367.36 65.16 -2.20 0.28 72.69 70.6467.88 67.49 -0.39 -0.50 73.22 72.33568.89 64.5 -4.39 -0.13 74.17 69.28

Source:StaffestimatesbasedonENNIV(1994,1997).

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Comparingthe1994and1997surveysshowsconsiderablechangesinthevalueoffooddonationsrecordedbythehouseholdsurvey.In1997prices,totalestimatedfooddonationsin1994were180millionsoles,58whilethetotalestimatedbenefitsoffoodprogramswas1.3billionsolesin1997.59Thesearelowestimatesfor1994butveryhighestimatesfor1997.

WeincludedfooddonationsinadifferentformthanCuántofor1997.Firstandmostimportant,Cuántomultiplieddailyfooddonationreceiptsby365toobtainannualvalues.However,severalofthedonationprogramsdonotworkeverydayperweekandcertainlynotallweeksperyear.ThemostimportantoneistheschoolbreakfastprogramwhichoperatesfromMondaytoFridayandabout2/3ofthewholeyear.Also,comedorespopularesandClubdeMadrefooddistributionpointsaregenerallyoperatedfromMondaytoFriday,andsometimesalsoonSaturday.Second,itbecomesclearstudyingthedatathatmanyrespondinghouseholdswereconfusedastowhethertheyweresupposedtogivethe(a)dailyvalueofdonationsreceived;or(b)thevaluefortheentirerecallperiod.Forexample,manyhouseholdsrespondedthattheyobtainedfivetimesaGlassofMilkfortwochildreninarecallperiodofaweekandtheylisted10solesasthevaluetheyreceived.Obviously,thevaluemustrefertothetotalofthefivetimestwomilkrationsreceivedratherthantoasingleglass(10soleswasabout4dollarsatthetimeofthesurvey).Initsestimates,Cuántointerpretedthese10solesasthedailyvalueofoneglassofmilk,whichwasreceived365timesayear-henceaddingaboutUS$1,600totheexpenditureoftheparticularhouseholds.Inourapproach,wecalculatedthemedianvalueofoneglassofmilkorschoollunchperregionandusedthisvaluetoestimatethevalueoftheseitemsforthehouseholds.Weassumedthatschoolsoperatefivetimesaweekand8monthsayear.TheGlassofMilkprogramwasassumedtowork5timesaweekduringthewholeyear.Makingthese

adjustments,ourestimateoftotalfoodaidin1997droppedfrom1.3billionsoles(Cuánto)to800billionsoles-afiguremuchmoreinlinewithexpenditurereportsofthelargenutritionprograms.60

Asshowninthemainbodyofthisstudywhendiscussingsocialexpenditures,theinclusionorexclusionoffoodaidhasamarkedimpactoncalculatedpovertyrates,especiallyintheruralhighlands.Theseverepovertyratewouldhavebeenthreepercenthigherhadweexcludedthedonations.Povertycalculationsarequitesensitivetochangesindefinitionshere,andfurtherin-depthanalysesfromotherresearcherswouldbewelcome.

58Thesurveycodein1994isal02=09.59Thesurveycodesin1997areah1=501505,507508.60Forthemeasurementofwelfareandpoverty,aproblemneverthelessremainssincethereseemstohavebeenanunderestimationoffooddonationsin1994.Hence,weareoverestimatingwelfareimprovementsbyincludingfoodaid.Ontheotherhand,hadweleftfooddonationsasidewhileinrealitytheyhadincreased,wewouldhaveunderestimatedwelfareincreases.

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Income

Fortheinequalitycomparisons,weuseadefinitionofincomesimilartothatofCuántoexceptinoneimportantaspect:Tomaintaincomparabilityinincomedefinitionsbetween1994and1997,weprefertousemonetaryincome.Monetaryincomeincludesfourclearlydefinedincomecategories(self-employedincome,wages,transfersandpropertyincome).Monetaryincomeexcludesself-consumption,imputedrent,andsomemiscellaneousincomecategoriesasdefinedbyCuánto.Thelatterthreecategoriesappeartobelesscomparablebetween1994and1997fortworeasons.First,therearedifferencesinthequestionsasked,andtheyareimportantincalculatingself-consumptionandimputedrent.Second,Cuántohasdifferentdefinitionsoftotalincomeforeachyear.Forexample,paymentstosocialsecurityonbehalfoftheemployeedonotappearinbothyears.Intermsofincomelevels,theexclusionofimputedrentmakesthebiggestdifferenceinestimatingnewincomelevelsbecauseimputedrentissuchalargecomponentofCuántoincomedefinitions.61Imputedrentrepresentedaround12to15percentoffamilyincome(innominalsoles,imputedrentcorrespondedto$1,674outofaweightedaverageincomeof$11,071in1994;and,$2,065outofanweightedaverageincomeof$17,924in1997).

PovertyLines&PriceDeflation

FoodBasketandValuein1994.TheCuántosurveysdidnotcollectquantityorpriceinformationintheconsumptionmodule.Thishasimportantimplicationsforthederivationofpovertylines:itimpliesthatthecompositionofthebasicfoodbasketcannotbederivedfromthesurveyitselfandhastobeobtainedfromanexternalsource.WeusethebasicfoodbasketfromCuánto(seeMoncadaandWebb1996)asthestartingpointofouranalysis.Itispricedin1994and1997usingdetailedregionalpriceindicessuppliedbytheStatistical

Institute,INEI.

Non-FoodBasketandValuein1994,PovertyLinein1994.DifferentfromcommonpracticeinPeru,wekeepthebasketofnon-foodgoodsconstantovertime.ThisapproachhasbeensuggestedseveraltimesbyFrancke(1997)andgoesbacktotheargumentmadeearlierthatideallywewanttofixacertainwelfarelevel(associatedwithafixedbundleofgoods)overtime.Ininternationalpractice,thisseemstobethepreferredwayofperformingwelfarecomparisonsintime(FerreiraandLitchfield1998,MacIsaacandHentschel1996,Ravallion1994).Weuse1994asthereferenceyeartoderivethebasicconsumptionbundle.WeemploythevaluesofthreenormativefoodbasketsusedinPeruandtheirvalueandthenderivetheupperboundpovertylines.Forthisweuseasareferencegroupthepopulationthatspendsonfoodexactlyatthevalueofthefoodpovertyline.Thetotalexpenditureofthisgroupthenbecomestheupperboundpovertyline.Weightsforthenon-foodbasketcanbeconsequentlyderived(TableA2.5).

PovertyLinesin1997.Thefoodandnon-foodbasketsfrom1994werethenpricedin1997usingdatafromINEIregionaloffices.Wecomputedpriceindicesfornon-foodcategoriesfrompriceinformationprovidedbyINEIfor26citiesintheSierra,Coast,Selva

61Thefiguresoninequalitypresentedinthemainbodyofthisstudyalsodonottakeintoaccountothernon-cashincome.

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andLima.Foreachregion,wecalculatedtheaveragepriceindexandusedittovaluethe1994basketin1997.SinceINEIreportsonlyurbanprices,weassumedthattherelativepricerise(notitsabsolutelevel)betweenruralandurbanareasinallregionsisthesamebetweenthesurveyyears.

TableA2.5.DerivationofPovertyLines1,1994,1997Category Weights

1994AnnualValue,1994(June1994prices)

InflationOct.97/June

94

AnnualValue,1997(Oct.1997prices)

Limafood 0.630 911.04 1.302 1182.38clothing 0.049 70.67 1.37 96.60water,electricity

0.086 125.05 1.44 179.58

cleaning 0.027 39.12 1.38 53.78health 0.075 108.33 1.56 169.43transport 0.075 108.33 1.37 148.20education0.055 80.12 1.54 123.39other 0.004 11.44 1.31 14.99[povertyline]

1,454,10 1968.34

UrbanCoastfood 0.610 789.13 1.312 1032.75clothing 0.028 35.95 1.28 45.83water,electricity

0.111 143.91 1.36 195.00

cleaning 0.031 39.97 1.23 49.28health 0.052 66.96 1.42 94.75transport 0.065 83.83 1.23 102.78education0.061 79.55 1.45 115.66other 0.043 58.40 1.29 75.16[povertyline]

1,297.70 1,711.22

RuralCoastfood 0.660 700.07 1.312 917.47clothing 0.068 72.67 1.28 92.66water,electricity

0.041 44.03 1.36 59.66

cleaning 0.027 29.18 1.23 35.97health 0.066 70.32 1.42 99.50transport 0.064 67.86 1.23 83.20education0.032 33.88 1.45 49.26other 0.043 50.69 1.29 65.24[povertyline]

1,068.70 1,402.96

UrbanSierrafood 0.610 668.68 1.302 866.45clothing 0.049 53.58 1.29 69.32water,electricity

0.105 116.00 1.36 157.60

cleaning 0.029 31.82 1.23 39.24health 0.046 50.60 1.42 71.96transport 0.054 59.44 1.29 76.59education0.079 86.73 1.47 127.42other 0.030 37.95 1.31 49.76[povertyline]

1,104.80 1,458.34

RuralSierrafood 0.760 583.23 1.362 791.48clothing 0.063 48.03 1.29 62.14water,electricity

0.029 22.56 1.36 30.65

cleaning 0.034 26.17 1.23 32.26health 0.037 28.24 1.42 40.16transport 0.026 19.80 1.29 25.51education0.025 19.49 1.47 28.63other 0.026 19.79 1.31 25.95

[povertyline]

767.30 1,036.78

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TableA2.5.DerivationofPovertyLines,1994,1997(continued)Category Weights

1994Value1994

InflationOct-97/June-94

Value1997

UrbanSelvafood 0.650 702.99 1.312 922.57clothing 0.049 53.18 1.20 63.71water,electricity

0.097 104.10 1.27 131.79

cleaning 0.032 33.91 1.20 40.76health 0.051 54.79 1.42 77.80transport 0.043 55.33 1.26 69.83education 0.043 45.75 1.34 61.22other 0.028 26.45 1.20 31.60[povertyline] 1,076.50 1,399.27RuralSelvafood 0.730 647.511.362 880.23clothing 0.064 57.371.20 68.73water,electricity

0.018 15.611.27 19.77

cleaning 0.047 42.021.20 50.51health 0.049 44.071.42 62.58transport 0.050 44.161.26 55.73education 0.018 15.611.34 20.89other 0.025 25.831.20 30.87[povertyline] 892.20 1,189.31Povertylinesinallyearsarederivedusingthepovertybasketoftheyear1994.Consumptionisdefinedasoutlinedintheprevioussection(e.g.,totalconsumptionexcludesrentalvalueofthehome);productgroupdefinitionsfollowtheInstitutoCuánto.Thefoodsharein1994(byregion)isdeterminedbythedecileofthepopulationthatspendsonfoodproductsthevalueoftheexogenouslydeterminedfoodbasket(Moncada1996).Expendituresharesin1994refertothispopulationgroup.Wecalculatedpricechangesfornon-foodcategoriesbetweentwosurveyyearsusingINEIcitypriceindicesbybroadproductgroupfor26cities,calculatingaverageindicesbyregion.SineINEIreportsonlyurbanprices,weassumethatthepricerises(nottheirabsolute

level)inruralareasarethesameasintheirurbancounterparts.Priceindexoftheexogenouslygivenfoodbasketderivedfromdividingthenominalvalueofthebasketindifferentyears.Thevalueofthefoodbasketinallregionsin1994and1997wascalculatedbytheInstitutoCuánto.

PriceDeflation.Twopricedeflationswereapplied.First,wedeflatedpricesovertime,toadjustallnominalexpenditurevaluesinthe1994surveytothemonthofJuneandallnominalexpendituresinthe1997surveytothemonthofOctober.SuchadjustmentforinflationwascarriedoutbyCuántoandisincludedinthebasicdatabase.Second,ratherthanworkingwithsevendifferentpovertylines,weadjustedallhouseholdconsumption(andincome)valuestothepriceofLima.Forthisexerciseweusedthecomputedpovertylinesandpricedeflators,definingLimaas''1"andusingtheratiobetweentheLimapovertylineandeachindividualregionalpovertylineasadeflatorforregionalmonetaryvalues.Thisallowedustocomparewelfarelevelsamonghouseholdsdirectly.

DefinitionofSeverePovertyLine.Thelowerorseverepovertylineusedinthereportisnotstrictlycomparabletotheextremepovertylineusedinmostotherpovertystudies.Thisisforasimplereason.Asoutlinedatlengthabove,wehadtoexcludeseveralimportantconsumptioncomponentsfromouraggregateinordertoachievecomparabilitybetweenthe1994and1997surveys.Mostimportantoftheseexclusionswastherentvalue.Thedefinitionoftheextremepovertylineisgenerallythevalueofthefoodbasketalone.Extremepovertyrateswouldthenbethepercentageofthepopulationwhosetotalexpendituresisnotenoughtopurchasesuchabasicfoodbasket.However,ifwewereto

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applythisdefinitionhere,extremepovertyrateswouldbeseverelyinflatedsinceourtotalconsumptionaggregateislowerduetotheexclusionoftherent.Therefore,weoptedtoapplyanarbitraryseverepovertylinethatneverthelesshasthepropertyofbeingperfectlycomparableacrosstime.Wechosetwo-thirdsoftheupperpovertyline(atLimaprices)asthisrate.

RegionalPovertyEstimatesandStandardErrors

Aspointedoutatthebeginningofthisstudy,povertyestimatesderivedfromhouseholdsurveysarenot'exact'butcarryacertaindegreeofinsecurityastheyarederivedforafractionofthetotalpopulationofthecountry.TablesA2.6andA2.7recordthestandardandseverepovertystatistics(headcountrate,povertygapandpovertyseverity)bygeographicalregionfor1994and1997,includingtheestimatedstandarderrorsthattakeintoaccountstratificationandclusteringofsampledesign.

TableA2.6:Poverty:StatisticsandStandardErrors,byRegion,1994and1997

Area HeadcountRate PovertyGap PovertySeverity1994 1997 1994 1997 1994 1997

PERU 53.5(1.3)

49.0(1.2)

18.9(0.7)

15.9(0.6)

9.1(0.4)

6.9(0.3)

Lima 42.2(2.4)

34.1(2.1)

11.5(0.9)

8.5(0.8)

4.6(0.4)

3.1(0.4)

CoastUrban 51.9(3.8)

52.8(3.5)

17.7(1.8)

16.8(1.5)

8.2(1.0)

7.1(0.8)

CoastRural 64.4(4.9)

62.1(4.9)

25.7(3.1)

22.5(2.4)

12.9(2.1)

10.6(1.4)

SierraUrban 48.1(3.9)

36.2(3.6)

16.6(1.9)

11.6(1.6)

8.0(1.1)

5.1(0.8)

SierraRural 65.9(2.8)

64.6(2.8)

26.6(1.5)

23.5(1.6)

16.9(1.1)

10.9(0.9)

SelvaUrban 43.0 42.9 13.6 12.9 5.8 5.3

(3.9) 3.7 (1.8) (1.2) (0.9) (0.6)SelvaRural 72.1

(3.0)66.9(3.3)

29.7(2.3)

24.3(2.2)

15.3(1.6)

11.5(1.4)

StaffestimatesbasedonENNIV(1994,1997)

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TableA2.7:SeverePoverty:StatisticsandStandardErrors,byRegion,1994and1997Area HeadcountRate PovertyGap PovertySeverity

1994 1997 1994 1997 1994 1997PERU 18.8

(1.014.8(0.9)

5.0(0.4

3.2(0.3

2.0(0.2

1.0(0.1)

Lima 7.2(1.1)

5.4(1.1)

1.6(0.3

0.8(0.2)

0.5(0.1)

0.2(0.1)

CoastUrban 18.4(2.8)

14.(2.3) 4.1(0.7)

3.0(0.6)

1.4(0.3)

0.9(0.2)

CoastRural 27.0(4.9)

23.5(3.4)

7.9(1.9)

5.8(1.1)

2.9(0.8)

2.0(0.5)

SierraUrban 18.0(2.8)

10.9(2.3)

4.6(0.9)

2.5(0.7)

1.9(0.5)

0.8(0.3)

SierraRural 29.0(2.2)

24.4(2.8)

8.9(1.0)

5.4(0.7)

4.0(0.6)

1.8(0.3)

SelvaUrban 13.2(2.6)

10.2(1.8)

2.5(0.6)

2.1(0.4)

0.7(0.2)

0.7(0.2)

SelvaRural 33.4(3.8)

25.6(3.8)

9.2(1.6)

5.9(1.1)

3.8(0.9)

2.0(0.5)

StaffestimatesbasedonENNIV(1994,1997)

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SensitivityAnalyses

Thesensitivitytestsconcernedwhetherpovertyestimatespresentedinthemainbodyofthereportweresensitivetohouseholdcomposition,size,andthepovertylinechosen.Inthebaselineestimatespresentedabove,wecomparedthepercapitapovertylinetopercapitaconsumptionexpendituresinthedifferentyears.Althoughthisiscommonpracticeinpovertyanalysis,itisimportanttonotethatanumberofverystarkassumptionsarenecessarytoconductwelfarecomparisonsonthisbasis.

EquivalenceScales.Thefirsttestconcernedadultequivalencescales.ThefoodbasketusedinPeruwasdevelopedforatypicalfamilyoftwoadultsandthreechildren.Inthisprototypefamily,itwasassumedthatdifferenthouseholdmembershavedifferentnutritionalrequirements.Forfivemembers,thefoodbasketcontainsabout11,900caloriesfortheCoastandSelvaand13,200fortheSierra.Inbothcasesthepercapitarequirementsinthefamilyarelowerthanthe2,700caloriesthattheWorldHealthOrganizationclassifiesastheminimumcaloricintakeforanadultmale.62Hence,inthederivationofthebasicfoodbasket,children'sfoodrequirementsweregivenalowerimportancethanadultrequirements.

AlthoughthebasicfoodbasketinPerudoestakethedifferentneedsofhouseholdmembersintoaccount,ourbaselinepovertymeasurementdoesnottakeaccounthouseholdcomposition.Thisstemsfromthe(widelyapplied)shortcutofderivingonegeneralpercapita(food)povertylineandapplyingthistoallhouseholds.Forexample,aone-personhouseholdismeasuredagainstthispercapitafoodpovertylineanddeclaredpoorif(s)herecordsconsumptionexpendituresbelowthetreshhold-independentoftheperson'sageorsex.Similarly,aten-memberhouseholdwithninechildreninitwouldalsobemeasuredagainstthe(tentimes)percapitapovertyline,which

wasdevelopedforafamilyofquitedifferentcharacteristics.Hence,althoughderivedfromanormativeconceptthatdifferentpeoplehavedifferentnutritionalrequirements,thewaywemeasuredpovertyinthisstudyimplicitlyassignseverybodyanadultequivalenceweightofone.

Thepurewaytomeasurepovertywouldassigneachhouseholdinthedatasetanindividualpovertylinethatreflectstheuniquecompositionofthehousehold.Wetestedtowhatdegreeourpovertycomparisonsaredependentontheimplicitchoiceofanadultequivalencescaleof1.0.Wedidnotderiveanewexogenouspovertylineforanadultbutweconductedthefollowingexperiment:first,wechoseanequivalencescalethatisverydifferentfromtheoneinthebasescenarioandquiteoftenappliedinothercountries:1.0foradults,0.5forchildrenbetweenages5and14,and0.3forchildrenbelowage5.63Second,wethenchoseapovertylinethatresultsinthesamepercentageofthePeruvianpopulationbeingpoorin1994aswhenweusenoadjustmentforadultequivalencescales.Thisprovidestheadvantagethatwecancontrolfortheabsolutenumberofpoorandcannowassesstheimpactoftheadjustmentontheregionaldistributionofpoverty.

62Thepercapitarequirementsofthesefoodbasketsarehighininternationalcomparisons.ThefoodpovertylineintheCoastandSelvacorrespondsto2,380calories,intheSierrato2,640calories.InmostotherLatinAmericancountries,theaveragepercapitafoodrequirementsaresetatbetween2,100and2,200calories.63SeeHentschelandLanjouw(1996)forashortdiscussionofadultequivalencescaleranges.

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Explicitadjustmentforadultequivalencescalesdoesnotalterthedistributionofthepoororthechangeofpovertyfrom1994to1997verymuch.TableA2.8includestheresultsoftherobustnesstest.Thefirsttwodatacolumnsshowtherankingofthesevendifferentregionswithrespecttothesimpleheadcountrate-therankingisnotinfluencedbytheintroductionofadultequivalencescales(AES).Thethirdandfourthdatacolumnsshowthechangeinthepovertyratebetween1994and1997.Forallregionschangesgointhesamedirection,withtheurbanSierraandLimashowingsubstantialgainsinpovertyreduction.However,theruralCoastshowsamuchstrongerheadcountreductionratiowiththeadjustmentforequivalencescalesthenwithout.Here,familystructureschangedsignificantlyoverthethreeyears:theaveragehouseholdsizeinthepoorergroupsdecreased,possiblyduetooutmigrationtourbancenters.

TableA2.8:AdultEquivalenceScalesandPovertyRates,Peru1994and1997

rankingw/AES1997

rankingw/oAES1997

changeinpovertyw/AES9497

changeinpovertyw/oAES9497

National -Lima 1 1 -9.3 -8.3CoastUrban

4 4 -1.2 -0.5

CoastRural

5 5 -12.0 -4.3

SierraUrban

2 2 -14.5 -13.2

SierraRural

6 6 -6.1 -3.8

SelvaUrban

3 3 -0.5 -0.1

SelvaRural

7 7 -7.7 -6.4

EconomiesofScale.Thesecondrobustnesstestofourresultisconcernedwitheconomiesofscaleinconsumption.Here,wewanttotesttheassumptionthatlargerhouseholdshaveadistinctadvantageoversmallerhouseholdsastheycanbenefitfromsharingcommodities(suchasstoves,furniture,housinginfrastructure)orfrompurchasingproductsinbulk,whichmightbecheaper.However,economiesofscaleinconsumptionwouldpertaintolargerhouseholdsindependentoftheiragecompositionandarethereforequitedistinctfromadultequivalency,whichderivesfromthedifferingneedsofdifferenthouseholdmembers.Thereisnosingleagreeduponmethodtoestimateeconomiesofscaleinconsumption.64However,toassesstheimportanceofscaleconsumption,analystsoftenchooseavalueoftheta(thedegreeofeconomiesofscale)ofaround0.6.65

Inordertoassesstheimportanceofthescaleeffect,weconductthefollowingevaluation.Wechooseapovertylinethatproducesthesamenationalpovertyrateasifweweretousetheunadjusteddata.Havingidentifiedthesubsetofpoorandnon-poorhouseholdsinbothdatasets,wecalculatethepovertyriskperhouseholdsizeandcomparethescale-adjustedresultstothenon-adjustedresults.Theseare

GraphA2.1:EconomicsofScale,HouseholeSizeandPoverty

Risk,1997

64SeeLanjouwandRavallion(1995).65Thisderivesfromthetransformationofhouseholdexpenditures(E)intopercapitatermsasEpc=E/(nq)wherenisthehouseholdsizeandqisthescaleparameter.Withqequalto1,noscaleeconomiesareassumed.Thelowerq,thehigherthescaleeffect.